https://aclweb.org/aclwiki/api.php?action=feedcontributions&user=Tristan+Miller&feedformat=atomACL Wiki - User contributions [en]2024-03-29T12:01:05ZUser contributionsMediaWiki 1.35.2https://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12890Employment opportunities, postdoctoral positions, summer jobs2020-06-02T12:08:20Z<p>Tristan Miller: Summer internship in language technology, Austrian Research Institute for Artificial Intelligence, Vienna</p>
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== Summer internship in language technology, Austrian Research Institute for Artificial Intelligence, Vienna ==<br />
* Employer: [http://ofai.at Austrian Research Institute for Artificial Intelligence], Vienna<br />
* Title: Student intern<br />
* Specialty: Language technology, computer-assisted translation<br />
* Location: Vienna, Austria<br />
* Deadline: June 15, 2020<br />
* Date posted: June 2, 2020<br />
* Contact: [mailto:tristan.miller@ofai.at tristan.miller@ofai.at]<br />
<br />
The Language and Interaction Technologies Group of the Austrian Research Institute for Artificial Intelligence (OFAI) in Vienna is seeking a student intern for programming tasks in the field of natural language processing.<br />
<br />
The successful applicant will be responsible for helping to program the front and back ends of an interactive, graphical tool for computer-assisted translation of creative language. The work will be carried out in close cooperation with the project leader, within the framework of the FWF-funded project Computational Pun-derstanding: https://punderstanding.ofai.at/<br />
<br />
The position is a fixed-term one-month contract for 20 hours per week, with the possibility to extend the contract for additional months, subject to project requirements and satisfactory job performance. Remuneration will be in accordance with the standard student assistant salary for FWF projects: https://www.fwf.ac.at/en/research-funding/personnel-costs/<br />
<br />
'''Requirements:''' Applicants must demonstrate:<br />
<br />
* Good knowledge of English and German<br />
* Good programming skills in Java (or less preferably in Python)<br />
* Permission to work in Austria<br />
* Interest in linguistics, language technology, and/or natural language processing<br />
<br />
Previous experience in developing graphical user interfaces is a big plus.<br />
<br />
'''Application procedure:''' Applications, including a cover letter and a CV detailing previous academic work and programming experience, should be submitted via e-mail to Tristan Miller: [mailto:tristan.miller@ofai.at tristan.miller@ofai.at]<br />
<br />
Applications should be submitted by 15 June 2020. Applications received after this deadline will be considered if the position remains unfilled.<br />
<br />
== Postdoctoral Fellow Position in NLP in the Department of Population Health Sciences at Weill Cornell Medicine, New York City == <br />
* Employer: [https://phs.weill.cornell.edu/ Department of Population Health Sciences at Weill Cornell Medicine]<br />
* Title: Postdoctoral Fellow Position <br />
* Speciality: Biomedical Natural Language Processing<br />
* Location: New York City, USA<br />
* Deadline: Open until filled<br />
* Date posted: 14 May, 2020<br />
* Contact: Yifan Peng (yip4002@med.cornell.edu)<br />
<br />
A postdoctoral fellow position is available in the Dr. Yifan Peng's [https://pengyifan.com/ laboratory] in the Department of Population Health Sciences at Weill Cornell Medicine, starting Fall 2020. Our laboratory is primarily interested in developing and applying computational approaches to biomedical text data and medical images. Our research has focused on biomedical text mining (e.g., BlueBERT, NegBio, LitVar), medical image analysis (e.g., NIH Chest X-ray, DeepSeeNet), and their combination (e.g., TieNet). The successful applicant will work on a NIH-funded project. The goal of this research project is to use radiology-specific ontology, NLP, image analysis, and DL to construct a radiology-specific knowledge graph. For more details, please see the announcements [https://phs.weill.cornell.edu/about-us/career-opportunities/postdoctoral-fellow-position-nlp-andor-image-analysis here]. <br />
<br />
'''Qualifications''': Applicants must have training with a strong emphasis on text mining and/or image analysis. Preference will be given to individuals with expertise in big data/modeling and those with a strong interest in healthcare or life sciences. The position is open to graduating Ph.D., M.D. or M.D./Ph.D. students in Computer Science, Bioinformatics, Health informatics, or a related discipline. Current postdoctoral fellows with less than three years of postdoctoral experience are also welcomed. <br />
<br />
Appointments are initially for two years. The positions can be extended for one or two additional years at the end of the first year based on performance. Stipends are commensurate with research experience and education. <br />
<br />
'''To apply''': Please submit CV and one-page research statement to Dr. Yifan Peng (pengyifan.mail@gmail.com). Shortlisted candidates will have an online interview.<br />
<br />
Cornell University's Weill Cornell Medicine is located in Manhattan, New York, immediately adjacent to the Sloan Kettering Institute and Rockefeller University, and as such offers the exposure to a dynamic and vibrant scientific environment that provides unique and unparalleled research training opportunities, including seminars given by scientific leaders from throughout the world, exposure to diverse research programs, highly sophisticated core facilities, grant writing workshops, career exploration events and professional development workshops. Weill Cornell Medicine provides subsidized housing for eligible Postdocs.<br />
<br />
Weill Cornell Medicine is an equal opportunity employer committed to excellence through diversity and strongly encourages applications from all qualified applicants, including women and minorities.<br />
<br />
== Multiple PhD positions in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Multiple PhD positions <br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Multiple PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for multiple PhD student positions in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. For more details, please see the announcements [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] and [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
Idiap offers competitive salaries, a beautiful location, and a world-class AI research community. PhD students are registered at EPFL, Switzerland. Some of these positions are to work on the Swiss center of excellence (NCCR) project: Evolving Language.<br />
<br />
The ideal candidate should hold a Master-level degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing or machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online either [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] or [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
<br />
<br />
== Postdoctoral position in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Postdoctoral researcher<br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Postdoctoral position''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for a Postdoctoral researcher position in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. This position is to work on the Swiss center of excellence (NCCR) project: Evolving Language. For more details, please see the [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D announcement here]. <br />
<br />
The ideal candidate should hold a PhD degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing and machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D here]. <br />
<br />
<br />
<br />
== Postdoc in NLP, ITU Copenhagen (Denmark) ==<br />
* Employer: Department of Computer Science, IT University of Copenhagen, Denmark<br />
* Specialty: Natural language processing / Machine learning<br />
* Location: Copenhagen, Denmark<br />
* Deadline: 12 June 2020, at 23:59 CEST.<br />
* Contact: [mailto:ld@itu.dk Leon Derczynski] <br />
* Date posted: May 1st 2020<br />
* Start Date: August 1st 2020<br />
<br />
The IT University of Copenhagen invites applications for a postdoc position to research cross-domain and cross-language transfer methods for natural language processing. The ClinRead project at ITU Copenhagen, funded by the Novo Nordisk Foundation, needs a full time post-doctoral researcher in natural language processing starting 1 August 2020 latest. The position is funded for 12 months, with possible extension. 100% of the time is allocated to research activities.<br />
The project application domain is information extract over patient notes in clinical journals. This provides the scope to do basic research in transfer learning for NLP. More details are here: https://nlp.itu.dk/2019/12/13/clinread-understanding-clinical-notes-for-new-languages-novo-nordisk-foundation-grant-for-leon-derczynski/<br />
The project is led by Dr. Leon Strømberg-Derczynski, who is an Assistant Professor in Computer Science at ITU.<br />
<br />
'''Candidate'''<br />
<br />
* You must either: (a) hold a PhD in a discipline related to natural language processing; or (b) have an expected PhD award date (with evidence) before 31 January 2021, with all PhD documents submitted before 31 October 2020.<br />
* You need to have published academic publications in natural language processing.<br />
* Excellent written and spoken English language skills are required.<br />
* Applications from both industry and academia are welcome.<br />
* The project works with Danish data, so excellent proficiency in Danish is beneficial.<br />
<br />
'''Working in Copenhagen'''<br />
Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and well-functioning infrastructure. Living and working in Copenhagen will be a good<br />
experience for you and your family.<br />
<br />
'''General information'''<br />
The IT University of Copenhagen is a teaching and research university concerned with information technology (IT) and the opportunities it offers. The IT University has more than 160 full-time academics. Research and teaching in information technology spans all academic activities which involve computers including computer science, information and media sciences, humanities and social sciences, business impact and the commercialization of IT.<br />
Questions about the positions can be directed to Assistant Professor, Leon Strømberg-Derczynski, IT University of Copenhagen, leod@itu.dk.<br />
<br />
'''Salary'''<br />
Appointment and salary will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations (AC).<br />
<br />
'''Application procedure'''<br />
You can only apply for this position through our e-recruitment system. Apply by pushing the button "Apply for position" in the job announcement on our website: http://en.itu.dk/About-ITU/Vacancies.<br />
The IT University uses tests in connection with the recruitment process.<br />
<br />
* Application deadline: '''12 June 2020, at 23:59 CEST.'''<br />
<br />
The IT University invites all qualified researchers regardless of age, gender, religious affiliation or ethnic background to apply for the positions.<br />
<br />
Apply here: [https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181159&DepartmentId=3439&MediaId=5]<br />
<br />
== Postdoctoral Researcher, University of Memphis (USA) ==<br />
* Employer: Institute for Intelligent Systems, University of Memphis, USA<br />
* Specialty: Cognitive Science with an emphasis on language, learning, and/or AI<br />
* Location: Memphis, TN USA<br />
* Deadline: open until filled<br />
* Contact: [mailto:aolney@memphis.edu Andrew Olney] <br />
* Date posted: March 5th 2020<br />
* Start Date: May 1st 2020<br />
<br />
The Institute for Intelligent Systems at The University of Memphis invites applications for a postdoctoral researcher. The 12-month position will start in May 2020 pending the availability of funds. Candidates must have a Ph.D. in hand by May 2020 and must have a compelling record of research success and potential. <br />
<br />
The successful candidate will complement interdisciplinary research at the IIS in one or more of the following focus areas: learning, language, and artificial intelligence. Candidates are encouraged to work on their own research agenda but may join existing projects. Mentoring will be provided based on research focus. Candidates from minority and underrepresented groups are highly encouraged to apply. Salary is competitive and commensurate with qualifications and experience. <br />
<br />
Please submit a letter detailing current research interests, a curriculum vitae, three representative publications, and email addresses for three professional references on-line at https://workforum.memphis.edu. For all other inquiries please contact Andrew Olney, aolney@memphis.edu. Review of applications will begin on March 1, 2020. <br />
<br />
A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce. <br />
<br />
== Two Research Fellows in Natural Language Processing, Artificial Intelligence Research Centre, Japan ==<br />
* Employer: Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining, UK<br />
* Specialty: Natural Language Processing, Information Extraction, Knowledge Discovery<br />
* Location: Tokyo, Japan<br />
* Deadline: 31st March 2020<br />
* Contact: [mailto:Sophia.ananiadou@manchester.ac.uk Sophia Ananiadou] <br />
* Date posted: March 4th 2020<br />
* Start Date: ASAP<br />
<br />
The Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining (UK) invite applications for two Research Fellows in Natural Language Processing. This is an exciting opportunity for two ambitious researchers to work on a major interdisciplinary project on Cancer, funded by the Japan Agency for Medical Research and Development. The posts aim to promote novel research into information extraction and knowledge discovery for immunotherapy for cancer mechanisms. The two fellows will work together and will also collaborate with NLP researchers both in Japan and in the UK, as well as with data scientists and medical practitioners in Japan.<br />
<br />
Although the posts will be located in AIRC, Japan (https://www.airc.aist.go.jp/en/intro/), the NLP research will be carried out in collaboration with the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), Department of Computer Science at The University of Manchester. The successful candidates will benefit from the vibrant research environments of both AIRC and NaCTeM.<br />
<br />
'''Essential skills''': candidates should have a PhD in Computer Science with an emphasis on Natural Language Processing/Machine Learning. They should have excellent knowledge of neural network architectures for NLP, information extraction (relation and event extraction) at scale, unsupervised learning or distant learning. Good programming skills (Perl, Python or other scripting languages) are highly desirable. Candidates should have a proven publication track record in high quality venues (e.g. ACL, EMNLP, AAAI, NAACL, etc.). Fluency in English is a must. They should have good written skills in English, be able to communicate with the partners of the consortium and work independently to meet deadlines.<br />
<br />
Applicants should send a detailed CV, including a list of publications, a covering letter indicating their expertise for this project and the names of three referees, to Professor Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk).<br />
<br />
Interviews will be held during the first week of April 2020, with the aim of starting the project as soon as possible. <br />
<br />
'''Salary''': ~6M yen to 9M yen per year (£43K to £65K), depending on experience. <br />
<br />
'''Duration of posts''': 3 years.<br />
<br />
== Postdoc in Computational Neurolinguistics, University of Georgia (USA) ==<br />
* Employer: Department of Linguistics, University of Georgia, Athens GA USA<br />
* Specialty: Natural Language Processing, Human Neuroimaging, Cognitive Science<br />
* Location: Athens, Georgia USA<br />
* Deadline: open until filled<br />
* Contact: [https://linguistics.uga.edu/directory/people/john-hale John Hale] <br />
* Date posted: March 2nd 2020<br />
* Start Date: August 1st 2020<br />
<br />
Duties include using tools and techniques from computational linguistics to analyze neural signals across languages. The successful candidate will work closely with partners in [https://sites.lsa.umich.edu/cnllab/ Michigan], at [http://www.paris-neuroscience.fr/en/centre-de-recherche/neurospin Neurospin], [https://www.inria.fr/en/centre/paris INRIA] and the [https://www.cbs.mpg.de/en MPI]. Apply at [https://www.ugajobsearch.com/postings/83958 https://www.ugajobsearch.com/postings/83958]<br />
<br />
== Postdoctoral Researcher in NLP for healthcare, Vrije Universiteit Brussel (VUB) - imec, Belgium ==<br />
<br />
* Employer: [http://www.etrovub.be Electronics and Informatics (ETRO)], at Vrije Universiteit Brussel (VUB) - [https://www.imec-int.com/en/home imec], Belgium<br />
* Title: Postdoctoral Researcher in NLP for healthcare<br />
* Specialty: NLP, Machine Learning<br />
* Location: Brussels<br />
* Deadline: March 29, 2020<br />
* Date posted: February 25, 2020<br />
* Contact: [mailto:ndeligia@etrovub.be ndeligia@etrovub.be]<br />
<br />
The department of Electronics and Informatics (ETRO) at Vrije Universiteit Brussel (VUB) and imec in Belgium offers a postdoctoral position in NLP and machine learning.<br />
<br />
'''Description of the project:'''<br><br />
The successful candidate will work within the frame of a project, funded by the Brussels government, on NLP for healthcare. The project will acquire data from one of the largest hospitals in Brussels (UZ Brussels) and its aim is to perform automated clinical coding and nosocomial outbreak detection. To do so, two important aspects will be investigated: (i) multilingual NLP techniques and (ii) interpretation of NLP models to address tasks such as extreme classification and real-time prediction.<br />
<br />
'''Responsibilities:'''<br><br />
• Design and implement innovative algorithms within the aforementioned project, <br><br />
• Publish the results at top-tier venues in NLP (e.g., ACL) and machine learning (e.g., ICLR), and<br><br />
• Supervise junior researchers and support in teaching.<br />
<br />
'''Profile and requirements:'''<br><br />
• A PhD degree focusing on artificial intelligence, machine learning, and natural language processing or related;<br><br />
• An excellent academic record with publications in top-tier scientific journals (e.g., TACL) and conference proceedings (e.g., ACL, EMNLP, AAAI);<br><br />
• Proven programming experience (e.g., Python, C++);<br><br />
• Fluency in state-of-the-art machine learning frameworks (e.g., Tensorflow, PyTorch);<br><br />
• Fluency in English and excellent scientific writing and presentation skills;<br><br />
• Ability and will to support teaching and to (co-)supervise bachelor, master and PhD students.<br />
<br />
'''What we offer:'''<br><br />
• A two-year position which upon positive evaluation can be further extended;<br><br />
• A competitive salary (including holiday allowance) and benefits,<br><br />
• An international scientific environment driven by excellence in fundamental research,<br><br />
• Opportunities for travelling to conferences and research visits to international partner research groups (e.g., at Duke University, UCL)<br />
<br />
'''How to apply:'''<br><br />
Interested candidates should send: <br />
• a detailed curriculum vitae, <br><br />
• a motivation letter related to the position’s profile,<br><br />
• electronic copies of three key scientific publications, and<br><br />
• the names of two potential referees <br />
<br />
to the following contact person: [http://homepages.vub.ac.be/~ndeligia/ Prof. Dr. Nikolaos Deligiannis] via email at [mailto:ndeligia@etrovub.be ndeligia@etrovub.be] by March 29, 2020.<br />
<br />
'''About the team:'''<br><br />
The position is within Big Data team at the Department of Electronics and Informatics at Vrije Universiteit Brussel, Belgium. The team is also affiliated with imec, an international R&D and innovation hub in nanoelectronics and digital technologies. <br />
<br />
<br />
== Permanent research position in language technology at the Norwegian Computing Center, Oslo, Norway ==<br />
<br />
* Employer: [https://www.nr.no Norwegian Computing Center (NR)], Oslo, Norway<br />
* Title: Research Scientist<br />
* Specialty: Language Technology, NLP, Machine Learning<br />
* Location: Oslo, Norway<br />
* Deadline: February 23, 2020<br />
* Date posted: February 1, 2020<br />
* Contact: [mailto:pierre.lison@nr.no pierre.lison@nr.no]<br />
<br />
<br />
We have a vacancy for a permanent research position in language technology at the Norwegian Computing Center (NR) in Oslo, Norway. We seek candidates with broad expertise in the field of NLP and the ability to work on different types of R&D projects. The position will be associated with the SAMBA research department, which currently has 45 researchers.<br />
<br />
The researcher will be expected to participate in several research projects. In particular, we have recently initiated a large interdisciplinary research project on anonymization of textual data in collaboration with legal scholars, data security experts and researchers in health informatics. We also conduct research on spoken dialogue systems, human-robot interaction, multilingual language resources and information extraction on large amounts of texts. We also work closely with the University of Oslo, and many of our research projects are carried out in collaboration with various research groups in Norway and internationally.<br />
<br />
You must be interested in applied research in language technology and machine learning. The applicant must hold a doctorate in language technology or computational linguistics, or a master degree combined several years of research experience. In addition, you must have good programming skills and the ability to work both independently and in teams.<br />
<br />
Applicants must be fluent in English, both verbally and in writing. Knowledge of Norwegian or another Scandinavian language is an advantage, as several of our research projects focus on Norwegian text data. Experience in securing funding for R&D projects is also appreciated.<br />
<br />
For more information, please visit [https://www.finn.no/job/fulltime/ad.html?finnkode=169049472 the application website] (in Norwegian).<br />
<br />
'''We offer''':<br><br />
We offer a 100% permanent position, good salary conditions, pension and insurance schemes, flexible working hours, 5 weeks of holiday in addition to paid leave during Christmas and Easter, and our own staff canteen. Good training and development opportunities in an inspiring work environment together with colleagues in language technology, machine learning, statistical modelling and image analysis.<br />
<br />
The Norwegian Computing Center is located in Kristen Nygaard's house at the Research Park at Blindern in Oslo. Negotiable starting date. We look forward to hearing from you.<br />
<br />
'''About us''':<br><br />
Norsk Regnesentral (NR) is an independent, non-profit and non-profit private foundation that conducts contract research for business and public enterprises both in Norway and internationally. Our core research areas are statistical modelling, machine learning, artificial intelligence and ICT. Our clients are business and public administration, the EU and the Research Council of Norway.<br />
<br />
The institute has 85 employees and is one of Europe's largest research institute within applied statistics. Major applications are petroleum, finance and insurance, earth observation, climate and environment, fisheries and aquaculture, health, image analysis and artificial intelligence. Research in ICT include cybersecurity, smart sensors, e-inclusion and universal design.<br />
<br />
<br />
== PostDoc or PhD in Secure and Robust Natural Language Processing, UKP Lab, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
UKP Lab of the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "Secure and Robust NLP"<br />
(PostDoc- or PhD-level; for an initial term until the end of 2021) <br />
<br />
as part of the National Research Center for Applied Cybersecurity ATHENE [1]. We are part of the research mission "SenPAI-Security and Privacy in AI". While AI becomes more common as a tool for various security applications where data must be analysed, clustered or attributed, the security of the applied AI algorithms is often limited. Various research results in the past years show shortcomings of trained neural nets (NN) like the lack of robustness against targeted attacks. The focus of our contribution to SenPAI is in (i) An automatic penetration testing system for NLP: A modular toolkit with common strategies to attack NLP models. This toolkit allows the wide-spread evaluation of state-of-the-art and in-production NLP systems; and (ii) Robust training objectives for NLP systems: State-of-the-art learning systems are equipped with the automatic attack toolkit in order to generate more robust NLP models. The goal is to have NLP models which are robust against new, unseen attacks and which require a higher effort to bypass them.<br />
<br />
For this project, we are looking to hire a PostDoc or a PhD student with both a strong background in Natural Language Processing and a strong interest to contribute to applied security. We plan to cooperate with Fraunhofer SIT in Darmstadt and several other machine learning labs involved in SenPAI. The UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, security and AI for Social Good in general. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interest in secure and robust NLP. Prior experience with neural network architectures, security-related applications and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
[1] [https://www.athene-center.de/en/ https://www.athene-center.de/en/]<br />
<br />
<br />
<br />
== PhD or PostDoc in Natural Language Processing for the Social Good, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "NLP for the Social Good"<br />
(PhD- or PostDoc-level; for an initial term until the end of 2022) <br />
<br />
We are building a research profile in "Content Analytics for the Social Good" in close collaboration with multiple Machine Learning and Data Science labs as well as Social Science labs at the universities of Frankfurt and Mainz. To stregthen this profile, we are looking to hire a PhD student or a PostDoc with both a strong background in Natural Language Processing and a genuine interest to contribute to the Social Good, i.e. conduct research with decidedly positive impact on our society. Examples include privacy-aware NLP and large-scale text analysis to promote and enhance corporate social responsibility, public-policy making, or user empowerment under uncertainty. We specifically envisage cooperations with law and economics researchers and cutting-edge NLP research in low-resource scenarios. <br />
<br />
The position is situated in a larger research environment of the UKP Lab as a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general. We have recently hired several postdocs to build a focus on NLP for the Social Good. The immediate supervision for the advertised position will be provided by Dr. Ivan Habernal. The strategic long-term advice will be given by Prof. Iryna Gurevych.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interdisciplinary interest in Computational Social Science. Prior experience with neural network architectures, corpus development and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
== NLP Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: NLP, search, dialog, joint NLP+computer vision<br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: January 7, 2020<br />
*Contact: Franck Dernoncourt <[mailto:franck.dernoncourt@adobe.com franck.dernoncourt@adobe.com]><br />
<br />
We are looking for PhD students with background in NLP, search, dialog, or joint NLP+computer vision for a spring/summer/autumn, ~13-week research internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile). You can view our NLP publications on https://research.adobe.com/publications/?a=natural-language-processing&y</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12889Employment opportunities, postdoctoral positions, summer jobs2020-06-02T12:04:13Z<p>Tristan Miller: link to archives</p>
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<br />
== Postdoctoral Fellow Position in NLP in the Department of Population Health Sciences at Weill Cornell Medicine, New York City == <br />
* Employer: [https://phs.weill.cornell.edu/ Department of Population Health Sciences at Weill Cornell Medicine]<br />
* Title: Postdoctoral Fellow Position <br />
* Speciality: Biomedical Natural Language Processing<br />
* Location: New York City, USA<br />
* Deadline: Open until filled<br />
* Date posted: 14 May, 2020<br />
* Contact: Yifan Peng (yip4002@med.cornell.edu)<br />
<br />
A postdoctoral fellow position is available in the Dr. Yifan Peng's [https://pengyifan.com/ laboratory] in the Department of Population Health Sciences at Weill Cornell Medicine, starting Fall 2020. Our laboratory is primarily interested in developing and applying computational approaches to biomedical text data and medical images. Our research has focused on biomedical text mining (e.g., BlueBERT, NegBio, LitVar), medical image analysis (e.g., NIH Chest X-ray, DeepSeeNet), and their combination (e.g., TieNet). The successful applicant will work on a NIH-funded project. The goal of this research project is to use radiology-specific ontology, NLP, image analysis, and DL to construct a radiology-specific knowledge graph. For more details, please see the announcements [https://phs.weill.cornell.edu/about-us/career-opportunities/postdoctoral-fellow-position-nlp-andor-image-analysis here]. <br />
<br />
'''Qualifications''': Applicants must have training with a strong emphasis on text mining and/or image analysis. Preference will be given to individuals with expertise in big data/modeling and those with a strong interest in healthcare or life sciences. The position is open to graduating Ph.D., M.D. or M.D./Ph.D. students in Computer Science, Bioinformatics, Health informatics, or a related discipline. Current postdoctoral fellows with less than three years of postdoctoral experience are also welcomed. <br />
<br />
Appointments are initially for two years. The positions can be extended for one or two additional years at the end of the first year based on performance. Stipends are commensurate with research experience and education. <br />
<br />
'''To apply''': Please submit CV and one-page research statement to Dr. Yifan Peng (pengyifan.mail@gmail.com). Shortlisted candidates will have an online interview.<br />
<br />
Cornell University's Weill Cornell Medicine is located in Manhattan, New York, immediately adjacent to the Sloan Kettering Institute and Rockefeller University, and as such offers the exposure to a dynamic and vibrant scientific environment that provides unique and unparalleled research training opportunities, including seminars given by scientific leaders from throughout the world, exposure to diverse research programs, highly sophisticated core facilities, grant writing workshops, career exploration events and professional development workshops. Weill Cornell Medicine provides subsidized housing for eligible Postdocs.<br />
<br />
Weill Cornell Medicine is an equal opportunity employer committed to excellence through diversity and strongly encourages applications from all qualified applicants, including women and minorities.<br />
<br />
== Multiple PhD positions in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Multiple PhD positions <br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Multiple PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for multiple PhD student positions in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. For more details, please see the announcements [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] and [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
Idiap offers competitive salaries, a beautiful location, and a world-class AI research community. PhD students are registered at EPFL, Switzerland. Some of these positions are to work on the Swiss center of excellence (NCCR) project: Evolving Language.<br />
<br />
The ideal candidate should hold a Master-level degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing or machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online either [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] or [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
<br />
<br />
== Postdoctoral position in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Postdoctoral researcher<br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Postdoctoral position''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for a Postdoctoral researcher position in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. This position is to work on the Swiss center of excellence (NCCR) project: Evolving Language. For more details, please see the [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D announcement here]. <br />
<br />
The ideal candidate should hold a PhD degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing and machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D here]. <br />
<br />
<br />
<br />
== Postdoc in NLP, ITU Copenhagen (Denmark) ==<br />
* Employer: Department of Computer Science, IT University of Copenhagen, Denmark<br />
* Specialty: Natural language processing / Machine learning<br />
* Location: Copenhagen, Denmark<br />
* Deadline: 12 June 2020, at 23:59 CEST.<br />
* Contact: [mailto:ld@itu.dk Leon Derczynski] <br />
* Date posted: May 1st 2020<br />
* Start Date: August 1st 2020<br />
<br />
The IT University of Copenhagen invites applications for a postdoc position to research cross-domain and cross-language transfer methods for natural language processing. The ClinRead project at ITU Copenhagen, funded by the Novo Nordisk Foundation, needs a full time post-doctoral researcher in natural language processing starting 1 August 2020 latest. The position is funded for 12 months, with possible extension. 100% of the time is allocated to research activities.<br />
The project application domain is information extract over patient notes in clinical journals. This provides the scope to do basic research in transfer learning for NLP. More details are here: https://nlp.itu.dk/2019/12/13/clinread-understanding-clinical-notes-for-new-languages-novo-nordisk-foundation-grant-for-leon-derczynski/<br />
The project is led by Dr. Leon Strømberg-Derczynski, who is an Assistant Professor in Computer Science at ITU.<br />
<br />
'''Candidate'''<br />
<br />
* You must either: (a) hold a PhD in a discipline related to natural language processing; or (b) have an expected PhD award date (with evidence) before 31 January 2021, with all PhD documents submitted before 31 October 2020.<br />
* You need to have published academic publications in natural language processing.<br />
* Excellent written and spoken English language skills are required.<br />
* Applications from both industry and academia are welcome.<br />
* The project works with Danish data, so excellent proficiency in Danish is beneficial.<br />
<br />
'''Working in Copenhagen'''<br />
Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and well-functioning infrastructure. Living and working in Copenhagen will be a good<br />
experience for you and your family.<br />
<br />
'''General information'''<br />
The IT University of Copenhagen is a teaching and research university concerned with information technology (IT) and the opportunities it offers. The IT University has more than 160 full-time academics. Research and teaching in information technology spans all academic activities which involve computers including computer science, information and media sciences, humanities and social sciences, business impact and the commercialization of IT.<br />
Questions about the positions can be directed to Assistant Professor, Leon Strømberg-Derczynski, IT University of Copenhagen, leod@itu.dk.<br />
<br />
'''Salary'''<br />
Appointment and salary will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations (AC).<br />
<br />
'''Application procedure'''<br />
You can only apply for this position through our e-recruitment system. Apply by pushing the button "Apply for position" in the job announcement on our website: http://en.itu.dk/About-ITU/Vacancies.<br />
The IT University uses tests in connection with the recruitment process.<br />
<br />
* Application deadline: '''12 June 2020, at 23:59 CEST.'''<br />
<br />
The IT University invites all qualified researchers regardless of age, gender, religious affiliation or ethnic background to apply for the positions.<br />
<br />
Apply here: [https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181159&DepartmentId=3439&MediaId=5]<br />
<br />
== Postdoctoral Researcher, University of Memphis (USA) ==<br />
* Employer: Institute for Intelligent Systems, University of Memphis, USA<br />
* Specialty: Cognitive Science with an emphasis on language, learning, and/or AI<br />
* Location: Memphis, TN USA<br />
* Deadline: open until filled<br />
* Contact: [mailto:aolney@memphis.edu Andrew Olney] <br />
* Date posted: March 5th 2020<br />
* Start Date: May 1st 2020<br />
<br />
The Institute for Intelligent Systems at The University of Memphis invites applications for a postdoctoral researcher. The 12-month position will start in May 2020 pending the availability of funds. Candidates must have a Ph.D. in hand by May 2020 and must have a compelling record of research success and potential. <br />
<br />
The successful candidate will complement interdisciplinary research at the IIS in one or more of the following focus areas: learning, language, and artificial intelligence. Candidates are encouraged to work on their own research agenda but may join existing projects. Mentoring will be provided based on research focus. Candidates from minority and underrepresented groups are highly encouraged to apply. Salary is competitive and commensurate with qualifications and experience. <br />
<br />
Please submit a letter detailing current research interests, a curriculum vitae, three representative publications, and email addresses for three professional references on-line at https://workforum.memphis.edu. For all other inquiries please contact Andrew Olney, aolney@memphis.edu. Review of applications will begin on March 1, 2020. <br />
<br />
A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce. <br />
<br />
== Two Research Fellows in Natural Language Processing, Artificial Intelligence Research Centre, Japan ==<br />
* Employer: Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining, UK<br />
* Specialty: Natural Language Processing, Information Extraction, Knowledge Discovery<br />
* Location: Tokyo, Japan<br />
* Deadline: 31st March 2020<br />
* Contact: [mailto:Sophia.ananiadou@manchester.ac.uk Sophia Ananiadou] <br />
* Date posted: March 4th 2020<br />
* Start Date: ASAP<br />
<br />
The Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining (UK) invite applications for two Research Fellows in Natural Language Processing. This is an exciting opportunity for two ambitious researchers to work on a major interdisciplinary project on Cancer, funded by the Japan Agency for Medical Research and Development. The posts aim to promote novel research into information extraction and knowledge discovery for immunotherapy for cancer mechanisms. The two fellows will work together and will also collaborate with NLP researchers both in Japan and in the UK, as well as with data scientists and medical practitioners in Japan.<br />
<br />
Although the posts will be located in AIRC, Japan (https://www.airc.aist.go.jp/en/intro/), the NLP research will be carried out in collaboration with the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), Department of Computer Science at The University of Manchester. The successful candidates will benefit from the vibrant research environments of both AIRC and NaCTeM.<br />
<br />
'''Essential skills''': candidates should have a PhD in Computer Science with an emphasis on Natural Language Processing/Machine Learning. They should have excellent knowledge of neural network architectures for NLP, information extraction (relation and event extraction) at scale, unsupervised learning or distant learning. Good programming skills (Perl, Python or other scripting languages) are highly desirable. Candidates should have a proven publication track record in high quality venues (e.g. ACL, EMNLP, AAAI, NAACL, etc.). Fluency in English is a must. They should have good written skills in English, be able to communicate with the partners of the consortium and work independently to meet deadlines.<br />
<br />
Applicants should send a detailed CV, including a list of publications, a covering letter indicating their expertise for this project and the names of three referees, to Professor Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk).<br />
<br />
Interviews will be held during the first week of April 2020, with the aim of starting the project as soon as possible. <br />
<br />
'''Salary''': ~6M yen to 9M yen per year (£43K to £65K), depending on experience. <br />
<br />
'''Duration of posts''': 3 years.<br />
<br />
== Postdoc in Computational Neurolinguistics, University of Georgia (USA) ==<br />
* Employer: Department of Linguistics, University of Georgia, Athens GA USA<br />
* Specialty: Natural Language Processing, Human Neuroimaging, Cognitive Science<br />
* Location: Athens, Georgia USA<br />
* Deadline: open until filled<br />
* Contact: [https://linguistics.uga.edu/directory/people/john-hale John Hale] <br />
* Date posted: March 2nd 2020<br />
* Start Date: August 1st 2020<br />
<br />
Duties include using tools and techniques from computational linguistics to analyze neural signals across languages. The successful candidate will work closely with partners in [https://sites.lsa.umich.edu/cnllab/ Michigan], at [http://www.paris-neuroscience.fr/en/centre-de-recherche/neurospin Neurospin], [https://www.inria.fr/en/centre/paris INRIA] and the [https://www.cbs.mpg.de/en MPI]. Apply at [https://www.ugajobsearch.com/postings/83958 https://www.ugajobsearch.com/postings/83958]<br />
<br />
== Postdoctoral Researcher in NLP for healthcare, Vrije Universiteit Brussel (VUB) - imec, Belgium ==<br />
<br />
* Employer: [http://www.etrovub.be Electronics and Informatics (ETRO)], at Vrije Universiteit Brussel (VUB) - [https://www.imec-int.com/en/home imec], Belgium<br />
* Title: Postdoctoral Researcher in NLP for healthcare<br />
* Specialty: NLP, Machine Learning<br />
* Location: Brussels<br />
* Deadline: March 29, 2020<br />
* Date posted: February 25, 2020<br />
* Contact: [mailto:ndeligia@etrovub.be ndeligia@etrovub.be]<br />
<br />
The department of Electronics and Informatics (ETRO) at Vrije Universiteit Brussel (VUB) and imec in Belgium offers a postdoctoral position in NLP and machine learning.<br />
<br />
'''Description of the project:'''<br><br />
The successful candidate will work within the frame of a project, funded by the Brussels government, on NLP for healthcare. The project will acquire data from one of the largest hospitals in Brussels (UZ Brussels) and its aim is to perform automated clinical coding and nosocomial outbreak detection. To do so, two important aspects will be investigated: (i) multilingual NLP techniques and (ii) interpretation of NLP models to address tasks such as extreme classification and real-time prediction.<br />
<br />
'''Responsibilities:'''<br><br />
• Design and implement innovative algorithms within the aforementioned project, <br><br />
• Publish the results at top-tier venues in NLP (e.g., ACL) and machine learning (e.g., ICLR), and<br><br />
• Supervise junior researchers and support in teaching.<br />
<br />
'''Profile and requirements:'''<br><br />
• A PhD degree focusing on artificial intelligence, machine learning, and natural language processing or related;<br><br />
• An excellent academic record with publications in top-tier scientific journals (e.g., TACL) and conference proceedings (e.g., ACL, EMNLP, AAAI);<br><br />
• Proven programming experience (e.g., Python, C++);<br><br />
• Fluency in state-of-the-art machine learning frameworks (e.g., Tensorflow, PyTorch);<br><br />
• Fluency in English and excellent scientific writing and presentation skills;<br><br />
• Ability and will to support teaching and to (co-)supervise bachelor, master and PhD students.<br />
<br />
'''What we offer:'''<br><br />
• A two-year position which upon positive evaluation can be further extended;<br><br />
• A competitive salary (including holiday allowance) and benefits,<br><br />
• An international scientific environment driven by excellence in fundamental research,<br><br />
• Opportunities for travelling to conferences and research visits to international partner research groups (e.g., at Duke University, UCL)<br />
<br />
'''How to apply:'''<br><br />
Interested candidates should send: <br />
• a detailed curriculum vitae, <br><br />
• a motivation letter related to the position’s profile,<br><br />
• electronic copies of three key scientific publications, and<br><br />
• the names of two potential referees <br />
<br />
to the following contact person: [http://homepages.vub.ac.be/~ndeligia/ Prof. Dr. Nikolaos Deligiannis] via email at [mailto:ndeligia@etrovub.be ndeligia@etrovub.be] by March 29, 2020.<br />
<br />
'''About the team:'''<br><br />
The position is within Big Data team at the Department of Electronics and Informatics at Vrije Universiteit Brussel, Belgium. The team is also affiliated with imec, an international R&D and innovation hub in nanoelectronics and digital technologies. <br />
<br />
<br />
== Permanent research position in language technology at the Norwegian Computing Center, Oslo, Norway ==<br />
<br />
* Employer: [https://www.nr.no Norwegian Computing Center (NR)], Oslo, Norway<br />
* Title: Research Scientist<br />
* Specialty: Language Technology, NLP, Machine Learning<br />
* Location: Oslo, Norway<br />
* Deadline: February 23, 2020<br />
* Date posted: February 1, 2020<br />
* Contact: [mailto:pierre.lison@nr.no pierre.lison@nr.no]<br />
<br />
<br />
We have a vacancy for a permanent research position in language technology at the Norwegian Computing Center (NR) in Oslo, Norway. We seek candidates with broad expertise in the field of NLP and the ability to work on different types of R&D projects. The position will be associated with the SAMBA research department, which currently has 45 researchers.<br />
<br />
The researcher will be expected to participate in several research projects. In particular, we have recently initiated a large interdisciplinary research project on anonymization of textual data in collaboration with legal scholars, data security experts and researchers in health informatics. We also conduct research on spoken dialogue systems, human-robot interaction, multilingual language resources and information extraction on large amounts of texts. We also work closely with the University of Oslo, and many of our research projects are carried out in collaboration with various research groups in Norway and internationally.<br />
<br />
You must be interested in applied research in language technology and machine learning. The applicant must hold a doctorate in language technology or computational linguistics, or a master degree combined several years of research experience. In addition, you must have good programming skills and the ability to work both independently and in teams.<br />
<br />
Applicants must be fluent in English, both verbally and in writing. Knowledge of Norwegian or another Scandinavian language is an advantage, as several of our research projects focus on Norwegian text data. Experience in securing funding for R&D projects is also appreciated.<br />
<br />
For more information, please visit [https://www.finn.no/job/fulltime/ad.html?finnkode=169049472 the application website] (in Norwegian).<br />
<br />
'''We offer''':<br><br />
We offer a 100% permanent position, good salary conditions, pension and insurance schemes, flexible working hours, 5 weeks of holiday in addition to paid leave during Christmas and Easter, and our own staff canteen. Good training and development opportunities in an inspiring work environment together with colleagues in language technology, machine learning, statistical modelling and image analysis.<br />
<br />
The Norwegian Computing Center is located in Kristen Nygaard's house at the Research Park at Blindern in Oslo. Negotiable starting date. We look forward to hearing from you.<br />
<br />
'''About us''':<br><br />
Norsk Regnesentral (NR) is an independent, non-profit and non-profit private foundation that conducts contract research for business and public enterprises both in Norway and internationally. Our core research areas are statistical modelling, machine learning, artificial intelligence and ICT. Our clients are business and public administration, the EU and the Research Council of Norway.<br />
<br />
The institute has 85 employees and is one of Europe's largest research institute within applied statistics. Major applications are petroleum, finance and insurance, earth observation, climate and environment, fisheries and aquaculture, health, image analysis and artificial intelligence. Research in ICT include cybersecurity, smart sensors, e-inclusion and universal design.<br />
<br />
<br />
== PostDoc or PhD in Secure and Robust Natural Language Processing, UKP Lab, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
UKP Lab of the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "Secure and Robust NLP"<br />
(PostDoc- or PhD-level; for an initial term until the end of 2021) <br />
<br />
as part of the National Research Center for Applied Cybersecurity ATHENE [1]. We are part of the research mission "SenPAI-Security and Privacy in AI". While AI becomes more common as a tool for various security applications where data must be analysed, clustered or attributed, the security of the applied AI algorithms is often limited. Various research results in the past years show shortcomings of trained neural nets (NN) like the lack of robustness against targeted attacks. The focus of our contribution to SenPAI is in (i) An automatic penetration testing system for NLP: A modular toolkit with common strategies to attack NLP models. This toolkit allows the wide-spread evaluation of state-of-the-art and in-production NLP systems; and (ii) Robust training objectives for NLP systems: State-of-the-art learning systems are equipped with the automatic attack toolkit in order to generate more robust NLP models. The goal is to have NLP models which are robust against new, unseen attacks and which require a higher effort to bypass them.<br />
<br />
For this project, we are looking to hire a PostDoc or a PhD student with both a strong background in Natural Language Processing and a strong interest to contribute to applied security. We plan to cooperate with Fraunhofer SIT in Darmstadt and several other machine learning labs involved in SenPAI. The UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, security and AI for Social Good in general. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interest in secure and robust NLP. Prior experience with neural network architectures, security-related applications and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
[1] [https://www.athene-center.de/en/ https://www.athene-center.de/en/]<br />
<br />
<br />
<br />
== PhD or PostDoc in Natural Language Processing for the Social Good, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "NLP for the Social Good"<br />
(PhD- or PostDoc-level; for an initial term until the end of 2022) <br />
<br />
We are building a research profile in "Content Analytics for the Social Good" in close collaboration with multiple Machine Learning and Data Science labs as well as Social Science labs at the universities of Frankfurt and Mainz. To stregthen this profile, we are looking to hire a PhD student or a PostDoc with both a strong background in Natural Language Processing and a genuine interest to contribute to the Social Good, i.e. conduct research with decidedly positive impact on our society. Examples include privacy-aware NLP and large-scale text analysis to promote and enhance corporate social responsibility, public-policy making, or user empowerment under uncertainty. We specifically envisage cooperations with law and economics researchers and cutting-edge NLP research in low-resource scenarios. <br />
<br />
The position is situated in a larger research environment of the UKP Lab as a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general. We have recently hired several postdocs to build a focus on NLP for the Social Good. The immediate supervision for the advertised position will be provided by Dr. Ivan Habernal. The strategic long-term advice will be given by Prof. Iryna Gurevych.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interdisciplinary interest in Computational Social Science. Prior experience with neural network architectures, corpus development and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
== NLP Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: NLP, search, dialog, joint NLP+computer vision<br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: January 7, 2020<br />
*Contact: Franck Dernoncourt <[mailto:franck.dernoncourt@adobe.com franck.dernoncourt@adobe.com]><br />
<br />
We are looking for PhD students with background in NLP, search, dialog, or joint NLP+computer vision for a spring/summer/autumn, ~13-week research internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile). You can view our NLP publications on https://research.adobe.com/publications/?a=natural-language-processing&y</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12888Employment opportunities, postdoctoral positions, summer jobs2020-06-02T12:03:40Z<p>Tristan Miller: archive postings from 2018 and 2019</p>
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<br />
== Postdoctoral Fellow Position in NLP in the Department of Population Health Sciences at Weill Cornell Medicine, New York City == <br />
* Employer: [https://phs.weill.cornell.edu/ Department of Population Health Sciences at Weill Cornell Medicine]<br />
* Title: Postdoctoral Fellow Position <br />
* Speciality: Biomedical Natural Language Processing<br />
* Location: New York City, USA<br />
* Deadline: Open until filled<br />
* Date posted: 14 May, 2020<br />
* Contact: Yifan Peng (yip4002@med.cornell.edu)<br />
<br />
A postdoctoral fellow position is available in the Dr. Yifan Peng's [https://pengyifan.com/ laboratory] in the Department of Population Health Sciences at Weill Cornell Medicine, starting Fall 2020. Our laboratory is primarily interested in developing and applying computational approaches to biomedical text data and medical images. Our research has focused on biomedical text mining (e.g., BlueBERT, NegBio, LitVar), medical image analysis (e.g., NIH Chest X-ray, DeepSeeNet), and their combination (e.g., TieNet). The successful applicant will work on a NIH-funded project. The goal of this research project is to use radiology-specific ontology, NLP, image analysis, and DL to construct a radiology-specific knowledge graph. For more details, please see the announcements [https://phs.weill.cornell.edu/about-us/career-opportunities/postdoctoral-fellow-position-nlp-andor-image-analysis here]. <br />
<br />
'''Qualifications''': Applicants must have training with a strong emphasis on text mining and/or image analysis. Preference will be given to individuals with expertise in big data/modeling and those with a strong interest in healthcare or life sciences. The position is open to graduating Ph.D., M.D. or M.D./Ph.D. students in Computer Science, Bioinformatics, Health informatics, or a related discipline. Current postdoctoral fellows with less than three years of postdoctoral experience are also welcomed. <br />
<br />
Appointments are initially for two years. The positions can be extended for one or two additional years at the end of the first year based on performance. Stipends are commensurate with research experience and education. <br />
<br />
'''To apply''': Please submit CV and one-page research statement to Dr. Yifan Peng (pengyifan.mail@gmail.com). Shortlisted candidates will have an online interview.<br />
<br />
Cornell University's Weill Cornell Medicine is located in Manhattan, New York, immediately adjacent to the Sloan Kettering Institute and Rockefeller University, and as such offers the exposure to a dynamic and vibrant scientific environment that provides unique and unparalleled research training opportunities, including seminars given by scientific leaders from throughout the world, exposure to diverse research programs, highly sophisticated core facilities, grant writing workshops, career exploration events and professional development workshops. Weill Cornell Medicine provides subsidized housing for eligible Postdocs.<br />
<br />
Weill Cornell Medicine is an equal opportunity employer committed to excellence through diversity and strongly encourages applications from all qualified applicants, including women and minorities.<br />
<br />
== Multiple PhD positions in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Multiple PhD positions <br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Multiple PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for multiple PhD student positions in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. For more details, please see the announcements [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] and [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
Idiap offers competitive salaries, a beautiful location, and a world-class AI research community. PhD students are registered at EPFL, Switzerland. Some of these positions are to work on the Swiss center of excellence (NCCR) project: Evolving Language.<br />
<br />
The ideal candidate should hold a Master-level degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing or machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online either [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710292%27%7D here] or [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710290%27%7D here].<br />
<br />
<br />
<br />
== Postdoctoral position in deep learning for natural language understanding at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Postdoctoral researcher<br />
* Speciality: Natural Language Understanding, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: 31 May, 2020<br />
* Date posted: 8 May, 2020<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Postdoctoral position''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for a Postdoctoral researcher position in the area of deep learning methods for natural language understanding, to work with Dr. James Henderson in the [https://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]. This position is to work on the Swiss center of excellence (NCCR) project: Evolving Language. For more details, please see the [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D announcement here]. <br />
<br />
The ideal candidate should hold a PhD degree in computer science, computational linguistics or related fields. She or he should have a background in natural language processing and machine learning, and should have strong programming skills.<br />
<br />
All questions related to these positions should be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online [https://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710291%27%7D here]. <br />
<br />
<br />
<br />
== Postdoc in NLP, ITU Copenhagen (Denmark) ==<br />
* Employer: Department of Computer Science, IT University of Copenhagen, Denmark<br />
* Specialty: Natural language processing / Machine learning<br />
* Location: Copenhagen, Denmark<br />
* Deadline: 12 June 2020, at 23:59 CEST.<br />
* Contact: [mailto:ld@itu.dk Leon Derczynski] <br />
* Date posted: May 1st 2020<br />
* Start Date: August 1st 2020<br />
<br />
The IT University of Copenhagen invites applications for a postdoc position to research cross-domain and cross-language transfer methods for natural language processing. The ClinRead project at ITU Copenhagen, funded by the Novo Nordisk Foundation, needs a full time post-doctoral researcher in natural language processing starting 1 August 2020 latest. The position is funded for 12 months, with possible extension. 100% of the time is allocated to research activities.<br />
The project application domain is information extract over patient notes in clinical journals. This provides the scope to do basic research in transfer learning for NLP. More details are here: https://nlp.itu.dk/2019/12/13/clinread-understanding-clinical-notes-for-new-languages-novo-nordisk-foundation-grant-for-leon-derczynski/<br />
The project is led by Dr. Leon Strømberg-Derczynski, who is an Assistant Professor in Computer Science at ITU.<br />
<br />
'''Candidate'''<br />
<br />
* You must either: (a) hold a PhD in a discipline related to natural language processing; or (b) have an expected PhD award date (with evidence) before 31 January 2021, with all PhD documents submitted before 31 October 2020.<br />
* You need to have published academic publications in natural language processing.<br />
* Excellent written and spoken English language skills are required.<br />
* Applications from both industry and academia are welcome.<br />
* The project works with Danish data, so excellent proficiency in Danish is beneficial.<br />
<br />
'''Working in Copenhagen'''<br />
Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and well-functioning infrastructure. Living and working in Copenhagen will be a good<br />
experience for you and your family.<br />
<br />
'''General information'''<br />
The IT University of Copenhagen is a teaching and research university concerned with information technology (IT) and the opportunities it offers. The IT University has more than 160 full-time academics. Research and teaching in information technology spans all academic activities which involve computers including computer science, information and media sciences, humanities and social sciences, business impact and the commercialization of IT.<br />
Questions about the positions can be directed to Assistant Professor, Leon Strømberg-Derczynski, IT University of Copenhagen, leod@itu.dk.<br />
<br />
'''Salary'''<br />
Appointment and salary will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations (AC).<br />
<br />
'''Application procedure'''<br />
You can only apply for this position through our e-recruitment system. Apply by pushing the button "Apply for position" in the job announcement on our website: http://en.itu.dk/About-ITU/Vacancies.<br />
The IT University uses tests in connection with the recruitment process.<br />
<br />
* Application deadline: '''12 June 2020, at 23:59 CEST.'''<br />
<br />
The IT University invites all qualified researchers regardless of age, gender, religious affiliation or ethnic background to apply for the positions.<br />
<br />
Apply here: [https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181159&DepartmentId=3439&MediaId=5]<br />
<br />
== Postdoctoral Researcher, University of Memphis (USA) ==<br />
* Employer: Institute for Intelligent Systems, University of Memphis, USA<br />
* Specialty: Cognitive Science with an emphasis on language, learning, and/or AI<br />
* Location: Memphis, TN USA<br />
* Deadline: open until filled<br />
* Contact: [mailto:aolney@memphis.edu Andrew Olney] <br />
* Date posted: March 5th 2020<br />
* Start Date: May 1st 2020<br />
<br />
The Institute for Intelligent Systems at The University of Memphis invites applications for a postdoctoral researcher. The 12-month position will start in May 2020 pending the availability of funds. Candidates must have a Ph.D. in hand by May 2020 and must have a compelling record of research success and potential. <br />
<br />
The successful candidate will complement interdisciplinary research at the IIS in one or more of the following focus areas: learning, language, and artificial intelligence. Candidates are encouraged to work on their own research agenda but may join existing projects. Mentoring will be provided based on research focus. Candidates from minority and underrepresented groups are highly encouraged to apply. Salary is competitive and commensurate with qualifications and experience. <br />
<br />
Please submit a letter detailing current research interests, a curriculum vitae, three representative publications, and email addresses for three professional references on-line at https://workforum.memphis.edu. For all other inquiries please contact Andrew Olney, aolney@memphis.edu. Review of applications will begin on March 1, 2020. <br />
<br />
A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce. <br />
<br />
== Two Research Fellows in Natural Language Processing, Artificial Intelligence Research Centre, Japan ==<br />
* Employer: Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining, UK<br />
* Specialty: Natural Language Processing, Information Extraction, Knowledge Discovery<br />
* Location: Tokyo, Japan<br />
* Deadline: 31st March 2020<br />
* Contact: [mailto:Sophia.ananiadou@manchester.ac.uk Sophia Ananiadou] <br />
* Date posted: March 4th 2020<br />
* Start Date: ASAP<br />
<br />
The Artificial Intelligence Research Centre, Japan and the National Centre for Text Mining (UK) invite applications for two Research Fellows in Natural Language Processing. This is an exciting opportunity for two ambitious researchers to work on a major interdisciplinary project on Cancer, funded by the Japan Agency for Medical Research and Development. The posts aim to promote novel research into information extraction and knowledge discovery for immunotherapy for cancer mechanisms. The two fellows will work together and will also collaborate with NLP researchers both in Japan and in the UK, as well as with data scientists and medical practitioners in Japan.<br />
<br />
Although the posts will be located in AIRC, Japan (https://www.airc.aist.go.jp/en/intro/), the NLP research will be carried out in collaboration with the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), Department of Computer Science at The University of Manchester. The successful candidates will benefit from the vibrant research environments of both AIRC and NaCTeM.<br />
<br />
'''Essential skills''': candidates should have a PhD in Computer Science with an emphasis on Natural Language Processing/Machine Learning. They should have excellent knowledge of neural network architectures for NLP, information extraction (relation and event extraction) at scale, unsupervised learning or distant learning. Good programming skills (Perl, Python or other scripting languages) are highly desirable. Candidates should have a proven publication track record in high quality venues (e.g. ACL, EMNLP, AAAI, NAACL, etc.). Fluency in English is a must. They should have good written skills in English, be able to communicate with the partners of the consortium and work independently to meet deadlines.<br />
<br />
Applicants should send a detailed CV, including a list of publications, a covering letter indicating their expertise for this project and the names of three referees, to Professor Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk).<br />
<br />
Interviews will be held during the first week of April 2020, with the aim of starting the project as soon as possible. <br />
<br />
'''Salary''': ~6M yen to 9M yen per year (£43K to £65K), depending on experience. <br />
<br />
'''Duration of posts''': 3 years.<br />
<br />
== Postdoc in Computational Neurolinguistics, University of Georgia (USA) ==<br />
* Employer: Department of Linguistics, University of Georgia, Athens GA USA<br />
* Specialty: Natural Language Processing, Human Neuroimaging, Cognitive Science<br />
* Location: Athens, Georgia USA<br />
* Deadline: open until filled<br />
* Contact: [https://linguistics.uga.edu/directory/people/john-hale John Hale] <br />
* Date posted: March 2nd 2020<br />
* Start Date: August 1st 2020<br />
<br />
Duties include using tools and techniques from computational linguistics to analyze neural signals across languages. The successful candidate will work closely with partners in [https://sites.lsa.umich.edu/cnllab/ Michigan], at [http://www.paris-neuroscience.fr/en/centre-de-recherche/neurospin Neurospin], [https://www.inria.fr/en/centre/paris INRIA] and the [https://www.cbs.mpg.de/en MPI]. Apply at [https://www.ugajobsearch.com/postings/83958 https://www.ugajobsearch.com/postings/83958]<br />
<br />
== Postdoctoral Researcher in NLP for healthcare, Vrije Universiteit Brussel (VUB) - imec, Belgium ==<br />
<br />
* Employer: [http://www.etrovub.be Electronics and Informatics (ETRO)], at Vrije Universiteit Brussel (VUB) - [https://www.imec-int.com/en/home imec], Belgium<br />
* Title: Postdoctoral Researcher in NLP for healthcare<br />
* Specialty: NLP, Machine Learning<br />
* Location: Brussels<br />
* Deadline: March 29, 2020<br />
* Date posted: February 25, 2020<br />
* Contact: [mailto:ndeligia@etrovub.be ndeligia@etrovub.be]<br />
<br />
The department of Electronics and Informatics (ETRO) at Vrije Universiteit Brussel (VUB) and imec in Belgium offers a postdoctoral position in NLP and machine learning.<br />
<br />
'''Description of the project:'''<br><br />
The successful candidate will work within the frame of a project, funded by the Brussels government, on NLP for healthcare. The project will acquire data from one of the largest hospitals in Brussels (UZ Brussels) and its aim is to perform automated clinical coding and nosocomial outbreak detection. To do so, two important aspects will be investigated: (i) multilingual NLP techniques and (ii) interpretation of NLP models to address tasks such as extreme classification and real-time prediction.<br />
<br />
'''Responsibilities:'''<br><br />
• Design and implement innovative algorithms within the aforementioned project, <br><br />
• Publish the results at top-tier venues in NLP (e.g., ACL) and machine learning (e.g., ICLR), and<br><br />
• Supervise junior researchers and support in teaching.<br />
<br />
'''Profile and requirements:'''<br><br />
• A PhD degree focusing on artificial intelligence, machine learning, and natural language processing or related;<br><br />
• An excellent academic record with publications in top-tier scientific journals (e.g., TACL) and conference proceedings (e.g., ACL, EMNLP, AAAI);<br><br />
• Proven programming experience (e.g., Python, C++);<br><br />
• Fluency in state-of-the-art machine learning frameworks (e.g., Tensorflow, PyTorch);<br><br />
• Fluency in English and excellent scientific writing and presentation skills;<br><br />
• Ability and will to support teaching and to (co-)supervise bachelor, master and PhD students.<br />
<br />
'''What we offer:'''<br><br />
• A two-year position which upon positive evaluation can be further extended;<br><br />
• A competitive salary (including holiday allowance) and benefits,<br><br />
• An international scientific environment driven by excellence in fundamental research,<br><br />
• Opportunities for travelling to conferences and research visits to international partner research groups (e.g., at Duke University, UCL)<br />
<br />
'''How to apply:'''<br><br />
Interested candidates should send: <br />
• a detailed curriculum vitae, <br><br />
• a motivation letter related to the position’s profile,<br><br />
• electronic copies of three key scientific publications, and<br><br />
• the names of two potential referees <br />
<br />
to the following contact person: [http://homepages.vub.ac.be/~ndeligia/ Prof. Dr. Nikolaos Deligiannis] via email at [mailto:ndeligia@etrovub.be ndeligia@etrovub.be] by March 29, 2020.<br />
<br />
'''About the team:'''<br><br />
The position is within Big Data team at the Department of Electronics and Informatics at Vrije Universiteit Brussel, Belgium. The team is also affiliated with imec, an international R&D and innovation hub in nanoelectronics and digital technologies. <br />
<br />
<br />
== Permanent research position in language technology at the Norwegian Computing Center, Oslo, Norway ==<br />
<br />
* Employer: [https://www.nr.no Norwegian Computing Center (NR)], Oslo, Norway<br />
* Title: Research Scientist<br />
* Specialty: Language Technology, NLP, Machine Learning<br />
* Location: Oslo, Norway<br />
* Deadline: February 23, 2020<br />
* Date posted: February 1, 2020<br />
* Contact: [mailto:pierre.lison@nr.no pierre.lison@nr.no]<br />
<br />
<br />
We have a vacancy for a permanent research position in language technology at the Norwegian Computing Center (NR) in Oslo, Norway. We seek candidates with broad expertise in the field of NLP and the ability to work on different types of R&D projects. The position will be associated with the SAMBA research department, which currently has 45 researchers.<br />
<br />
The researcher will be expected to participate in several research projects. In particular, we have recently initiated a large interdisciplinary research project on anonymization of textual data in collaboration with legal scholars, data security experts and researchers in health informatics. We also conduct research on spoken dialogue systems, human-robot interaction, multilingual language resources and information extraction on large amounts of texts. We also work closely with the University of Oslo, and many of our research projects are carried out in collaboration with various research groups in Norway and internationally.<br />
<br />
You must be interested in applied research in language technology and machine learning. The applicant must hold a doctorate in language technology or computational linguistics, or a master degree combined several years of research experience. In addition, you must have good programming skills and the ability to work both independently and in teams.<br />
<br />
Applicants must be fluent in English, both verbally and in writing. Knowledge of Norwegian or another Scandinavian language is an advantage, as several of our research projects focus on Norwegian text data. Experience in securing funding for R&D projects is also appreciated.<br />
<br />
For more information, please visit [https://www.finn.no/job/fulltime/ad.html?finnkode=169049472 the application website] (in Norwegian).<br />
<br />
'''We offer''':<br><br />
We offer a 100% permanent position, good salary conditions, pension and insurance schemes, flexible working hours, 5 weeks of holiday in addition to paid leave during Christmas and Easter, and our own staff canteen. Good training and development opportunities in an inspiring work environment together with colleagues in language technology, machine learning, statistical modelling and image analysis.<br />
<br />
The Norwegian Computing Center is located in Kristen Nygaard's house at the Research Park at Blindern in Oslo. Negotiable starting date. We look forward to hearing from you.<br />
<br />
'''About us''':<br><br />
Norsk Regnesentral (NR) is an independent, non-profit and non-profit private foundation that conducts contract research for business and public enterprises both in Norway and internationally. Our core research areas are statistical modelling, machine learning, artificial intelligence and ICT. Our clients are business and public administration, the EU and the Research Council of Norway.<br />
<br />
The institute has 85 employees and is one of Europe's largest research institute within applied statistics. Major applications are petroleum, finance and insurance, earth observation, climate and environment, fisheries and aquaculture, health, image analysis and artificial intelligence. Research in ICT include cybersecurity, smart sensors, e-inclusion and universal design.<br />
<br />
<br />
== PostDoc or PhD in Secure and Robust Natural Language Processing, UKP Lab, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
UKP Lab of the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "Secure and Robust NLP"<br />
(PostDoc- or PhD-level; for an initial term until the end of 2021) <br />
<br />
as part of the National Research Center for Applied Cybersecurity ATHENE [1]. We are part of the research mission "SenPAI-Security and Privacy in AI". While AI becomes more common as a tool for various security applications where data must be analysed, clustered or attributed, the security of the applied AI algorithms is often limited. Various research results in the past years show shortcomings of trained neural nets (NN) like the lack of robustness against targeted attacks. The focus of our contribution to SenPAI is in (i) An automatic penetration testing system for NLP: A modular toolkit with common strategies to attack NLP models. This toolkit allows the wide-spread evaluation of state-of-the-art and in-production NLP systems; and (ii) Robust training objectives for NLP systems: State-of-the-art learning systems are equipped with the automatic attack toolkit in order to generate more robust NLP models. The goal is to have NLP models which are robust against new, unseen attacks and which require a higher effort to bypass them.<br />
<br />
For this project, we are looking to hire a PostDoc or a PhD student with both a strong background in Natural Language Processing and a strong interest to contribute to applied security. We plan to cooperate with Fraunhofer SIT in Darmstadt and several other machine learning labs involved in SenPAI. The UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, security and AI for Social Good in general. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interest in secure and robust NLP. Prior experience with neural network architectures, security-related applications and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
[1] [https://www.athene-center.de/en/ https://www.athene-center.de/en/]<br />
<br />
<br />
<br />
== PhD or PostDoc in Natural Language Processing for the Social Good, Computer Science Department, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: February 10, 2020<br />
* Date posted: January 20, 2020<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
Associate Research Scientist "NLP for the Social Good"<br />
(PhD- or PostDoc-level; for an initial term until the end of 2022) <br />
<br />
We are building a research profile in "Content Analytics for the Social Good" in close collaboration with multiple Machine Learning and Data Science labs as well as Social Science labs at the universities of Frankfurt and Mainz. To stregthen this profile, we are looking to hire a PhD student or a PostDoc with both a strong background in Natural Language Processing and a genuine interest to contribute to the Social Good, i.e. conduct research with decidedly positive impact on our society. Examples include privacy-aware NLP and large-scale text analysis to promote and enhance corporate social responsibility, public-policy making, or user empowerment under uncertainty. We specifically envisage cooperations with law and economics researchers and cutting-edge NLP research in low-resource scenarios. <br />
<br />
The position is situated in a larger research environment of the UKP Lab as a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general. We have recently hired several postdocs to build a focus on NLP for the Social Good. The immediate supervision for the advertised position will be provided by Dr. Ivan Habernal. The strategic long-term advice will be given by Prof. Iryna Gurevych.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining and strong interdisciplinary interest in Computational Social Science. Prior experience with neural network architectures, corpus development and other relevant areas of NLP and Machine Learning is a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment.<br />
The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. <br />
The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. <br />
Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. <br />
UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. <br />
The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by February 10th, 2020: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
== NLP Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: NLP, search, dialog, joint NLP+computer vision<br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: January 7, 2020<br />
*Contact: Franck Dernoncourt <[mailto:franck.dernoncourt@adobe.com franck.dernoncourt@adobe.com]><br />
<br />
We are looking for PhD students with background in NLP, search, dialog, or joint NLP+computer vision for a spring/summer/autumn, ~13-week research internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile). You can view our NLP publications on https://research.adobe.com/publications/?a=natural-language-processing&y</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities_posted_2019&diff=12887Employment opportunities posted 20192020-06-02T12:03:38Z<p>Tristan Miller: Archived from Employment opportunities, postdoctoral positions, summer jobs</p>
<hr />
<div>* This is an archive of employment opportunities that were posted in 2019.<br />
<br />
== Postdoctoral Researcher in NLP, School of Informatics, University of Edinburgh ==<br />
* Employer: University of Edinburgh<br />
* Title: Form-Independent Semantics for Natural Language Understanding<br />
* Specialty: NLP<br />
* Location: Edinburgh, United Kingdom<br />
* Deadline: 14th January 2020 at 5pm GMT<br />
* Date posted: 21st December 2019<br />
* Contact: Prof. Mark Steedman [mailto:steedman@inf.ed.ac.uk steedman@inf.ed.ac.uk]<br />
<br />
The position is to collaborate on research in question-answering using entailment graphs built by machine-reading and deep learning in Mark Steedman's lab in the Institute for Language, Cognition, and Computation (ILCC) at Edinburgh.<br />
<br />
Details and application forms at: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=050766<br />
<br />
<br />
== PhD Position in Neural NLG, Nancy, France as part of the EU Funded NL4XAI Innovative Training Network ==<br />
* Employer: CNRS<br />
* Title: Explainable Models for Natural Language Generation<br />
* Specialty: NLP, AI, Deep Learning<br />
* Location: Nancy, France<br />
* Deadline: February 14, 2020, at 23h59 CET (UCT + 01:00)<br />
* Date posted: December 17, 2019<br />
* Contact: [mailto:claire.gardent@loria.fr claire.gardent@loria.fr]<br />
<br />
Estimated Starting Date: April 1, 2020<br />
<br />
For more information, see https://members.loria.fr/CGardent/explainable-nlg.pdf<br />
<br />
The EU funded NL4XAI Innovative Training Network is looking to employ a<br />
<br />
Research Associate / PhD Candidate <br />
in Deep Learning and Natural Language Generation<br />
<br />
The researcher will work under the supervision of Claire Gardent (https://members.loria.fr/CGardent/) at CNRS/LORIA/Lorraine University, Nancy (France) and be co-supervised by Albert Gatt (University of Malta); he or she will be expected to enrol for a PhD at Lorraine University (Nancy, France). Both Claire Gardent and Albert Gatt are leading experts on NLG. The researcher will be part of the Lorraine computer science research unit (LORIA) at Nancy, and work alongside other students and researchers who work on models for NLG. S/he will also benefit from the wider training and research network provided by the European NL4XAI Innovative Training Network (https://nl4xai.eu/).<br />
<br />
During the course of the project, the researcher will carry out two 3 months-secondments to the University of Malta (with Albert Gatt) and one 3-months secondment to Orange in Lanion, France (with Lina Rohas-Barahona).<br />
<br />
Claire Gardent has just been awarded an AI chair which focuses on multilingual and multisource NLG and will fund an additional 3 PhD students and an engineer over a period of 4 years (2020-2024). She also participates in the ANR Quantum Project on Question Generation (2019 – 2023) and heads the CNRS Research Network on Computational, Formal and Field Linguistics (2019 - 2023). <br />
<br />
This is a great opportunity to join a leading NLG research group and work with top researchers to develop innovative techniques for NLG and explainable AI!<br />
<br />
The NL4XAI project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860621.<br />
<br />
<br />
== 11 Early Stage Artificial Intelligence Research Positions available in NL4XAI project (H2020-MSCA-ITN) == <br />
* Employer: EU Funded NL4XAI Innovative Training Network <br />
* Title: 11 Early Stage Artificial Intelligence Research Positions available in NL4XAI project (H2020-MSCA-ITN)<br />
* Specialty: NLP, AI<br />
* Location: Europe <br />
* Deadline: February 14, 2020, at 23h59 CET (UCT + 01:00)<br />
* Date posted: December 17, 2019<br />
* Contact: [mailto:josemaria.alonso.moral@USC.ES josemaria.alonso.moral@USC.ES]<br />
<br />
Estimated Starting Date: April 1, 2020<br />
<br />
Eleven PhD positions are offered within the framework of NL4XAI: Interactive Natural Language Technology for Explainable Artificial Intelligence, a project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 860621.<br />
<br />
NL4XAI is a European Training Network (ETN) project, which will train 11 creative, entrepreneurial and innovative early-stage researchers (ESRs), who will face the challenge of making Artificial Intelligence (AI) self-explanatory and thus contribute to translating knowledge into products and services for economic and social benefit, with the support of Explainable AI (XAI) systems.<br />
<br />
The focus of NL4XAI is in the automatic generation of interactive explanations in natural language, just as humans naturally do, and as a complement to visualization tools. As a result, ESRs are expected to leverage the usage of AI models and techniques even by non-expert users.<br />
<br />
The NL4XAI consortium is made up of 18 partners and beneficiaries from 6 different European countries (France, Malta, Poland, Spain, The Netherlands and the United Kingdom). The consortium is coordinated by the Research Centre in Intelligent Technologies of the Univ. of Santiago de Compostela (CiTIUS-USC) and the partners correspond to 2 national R&D centres (IIIA-CSIC and CNRS-LORIA), 10 universities (Univ. Aberdeen, TU Delft, Univ. Malta, Utrecht Univ., Univ. Twente, Univ. Lorraine, Univ. Dundee, Univ. Autònoma de Barcelona, Univ. Santiago de Compostela and Warsaw Univ. of Technology) and 6 private companies (Indra, Accenture, Orange, Wizenoze, Arria and Info Support).<br />
<br />
Each ESR will work in an individual research project in a different host institution and will participate in academic and inter-sectoral secondments at the premises of other NL4XAI’s members.<br />
<br />
We look for outstanding, motivated and team-spirited candidates to carry out a PhD within the NL4XAI ETN and who will get unique international and inter-sectoral training from prominent European researchers (from both academy and industry).<br />
<br />
All details are available at:<br />
https://nl4xai.eu/<br />
<br />
<br />
The NL4XAI project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860621.<br />
<br />
<br />
== Natural Language Processing and Machine Learning Scientist (KTP Fellow) in Manchester, UK ==<br />
* Employer: VoiceIQ and The University of Manchester, UK<br />
* Title: Natural Language Processing and Machine Learning Scientist (KTP Fellow)<br />
* Specialty: NLP, Machine Learning<br />
* Location: Manchester, UK<br />
* Deadline: January 13, 2020<br />
* Date posted: December 11, 2019<br />
* Contact: [mailto:Sophia.Ananiadou@manchester.ac.uk Sophia.Ananiadou@manchester.ac.uk]<br />
<br />
This is an exciting opportunity for an ambitious research scientist with expertise in Natural Language Processing and Machine Learning with the ability and confidence to work on a 30-month Knowledge Transfer Partnership (KTP) project with VoiceIQ Limited. <br />
<br />
The project aims at developing innovative AI solutions to an exciting, high-impact and challenging problem of automatically detecting consumer vulnerability from communication channels by embedding state-of-the-art natural language processing and machine learning techniques.<br />
<br />
VoiceIQ is an AI-powered, communications system, transforming enterprise telephony by leveraging the power of machine learning and natural language processing. The University of Manchester is among the world’s best universities (World 33 by Academic Ranking of World Universities 2019, World 27 by QS 2020).<br />
<br />
The position will provide you with a unique opportunity to work in a rapidly growing UK based, AI software company and play a key role in the product development and commercial success of the company. You:<br />
<br />
- Will apply and improve state-of-the-art machine learning and natural language processing techniques to address a cutting edge business problem which has a high level of commercial applicability;<br />
<br />
- Will play a vital role in innovating, experimenting, developing and transferring such new techniques to VoiceIQ, publishing academic research discoveries in high impact fora in the field, and supporting strategically important future business development;<br />
<br />
- Ultimately, will be responsible for creating a product that is new, first to the market and that will help protect vulnerable members of society from falling prey to mis-selling.<br />
<br />
The position is particularly suitable for applicants who want to bridge academic and industrial research excellence.<br />
<br />
You will require a PhD degree with an emphasis on machine learning applied to natural language processing or relevant subjects, and a few years of post-doc (or equivalent) experience. Experience relevant to deep learning and neural network-based learning models, to either text or speech analytics is essential.<br />
<br />
This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and Industry.<br />
<br />
Based at VoiceIQ at Universal Square Business Centre in Manchester, the successful candidate will work directly with supervisors from both the University of Manchester and VoiceIQ and will use the facilities and resources of both organisations.<br />
<br />
As an equal opportunities employer we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.<br />
<br />
FURTHER DETAILS AND APPLICATION FORM - https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=18367<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, Machine Learning, Text Mining<br />
* Location: Darmstadt<br />
* Deadline: December 11, 2019<br />
* Date posted: November 14, 2019<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an <br />
<br />
Associate Research Scientist <br />
(PostDoc- or PhD-level; for an initial term of two years) <br />
<br />
We are looking to strengthen our group’s profile in a set of emerging areas of Machine Learning and Natural Language Processing (NLP). Examples include human-in-the-loop machine learning, argument mining and claim validaton, conversational AI, or multimodal commonsense reasoning. UKP Lab is a high-profile research group comprising over thirty team members who work on various aspects of data-driven NLP and machine learning. Their novel applications in various domains extend to mining scientific literature or social media, and AI for Social Good in general.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning, Natural Language Processing or Text Mining. Prior experience with neural network architectures, reinforcement learning and other relevant areas of NLP and Machine Learning are a plus. Demonstrable engagement in open source projects, strong programming skills and communication skills in English are highly appreciated.<br />
<br />
UKP Lab (cf. [https://www.informatik.tu-darmstadt.de https://www.informatik.tu-darmstadt.de]) provides a highly agile, diverse and supportive research environment. The lab has a wide cooperation network with both leading academic and industrial professionals in NLP and Machine Learning. The Department of Computer Science of the TU Darmstadt is regularly ranked among the top ones in respective rankings of the German universities. Its unique profile around AI (cf. [https://www.ai-da.tu-darmstadt.de https://www.ai-da.tu-darmstadt.de]) and information processing (cf. [https://www.informatik.tu-darmstadt.de/aiphes https://www.informatik.tu-darmstadt.de/aiphes]) emphasizes NLP, machine learning, and and their great potential for the industry and society at large. UKP Lab is committed to cutting-edge research, publishing in top-tier venues, cooperative work style and close interaction of all team members. The selected candidates enjoy numerous opportunities for professional growth, leading to successful faculty careers or exciting industrial employments.<br />
<br />
To apply, please provide a detailed CV, a motivation letter and an outline of previous work or research experience along with the names of up to three referees (if available). Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by December 11th, 2019: [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment]. Applications arriving after the deadline will still be considered until the position is filled.<br />
<br />
<br />
== Tenure-Track/Tenured Faculty Positions: The University of Texas at Arlington ==<br />
* Employer: Department of Computer Science and Engineering, The University of Texas at Arlington<br />
* Title: Assistant/Associate Professor<br />
* Speciality: AI / Machine Learning / Robotics, Cyber Physical Systems<br />
* Location: Arlington, TX, USA<br />
* Deadline: Review of applications will start November 15, 2019 and will continue until the positions are filled.<br />
* Contact: Christoph Csallner (csallner@uta.edu), Chengkai Li (cli@uta.edu)<br />
* Date posted: November 9, 2019<br />
* Website: https://cse.uta.edu/faculty-positions/tenure-track.php<br />
<br />
The Computer Science and Engineering Department at The University of Texas at Arlington invites applications for 3 tenure-track/tenured assistant/associate professor positions with a tentative start date in Fall 2020. The areas of the following position titles are intended to be interpreted broadly (e.g., "Cyber Physical Systems" may include embedded systems, hybrid systems, sensors, vision, IoT, cybersecurity, feedback systems, actuation, digital fabrication, and related areas):<br />
<br />
* Assistant/Associate Professor - AI / Machine Learning / Robotics<br />
* Assistant Professor - Cyber Physical Systems<br />
* Assistant/Associate Professor - Cyber Physical Systems<br />
<br />
Our key objective is to hire faculty members with outstanding qualifications, who share the university's core values of high standards of excellence in teaching, innovative research, and service, combined with fostering an open and inclusive environment and promoting diversity and participation of groups that are currently underrepresented in engineering fields. A major emphasis will be potential research collaboration within and outside the department.<br />
<br />
'''Application Instructions''' <br />
<br />
To apply, please go to https://uta.peopleadmin.com/postings/10800 and submit the following materials: cover letter, curriculum vitae, research plans, teaching philosophy, and contact information of at least three references (at least five references for Associate Professor candidates). Senior candidates should also include unofficial course evaluations. All candidates should also include a statement of contribution to diversity, equity, and inclusion.<br />
<br />
Review of applications will start November 15, 2019 and will continue until the positions are filled.<br />
<br />
Questions about the openings should be addressed to cli@uta.edu or csallner@uta.edu.<br />
<br />
'''EEO/AA Policy'''<br />
<br />
UTA is an Equal Opportunity/Affirmative Action institution. Minorities, women, veterans and persons with disabilities are encouraged to apply. Additionally, the University prohibits discrimination in employment on the basis of sexual orientation. A criminal background check will be conducted on finalists. UTA is a tobacco free campus.<br />
<br />
<br />
== Tenure Track Faculty Positions: Johns Hopkins University ==<br />
* Employer: Department of Computer Science, Johns Hopkins University<br />
* Title: Assistant/Associate/Full Professor<br />
* Speciality: All areas of Computer Science<br />
* Location: Baltimore, Maryland, USA<br />
* Deadline: December 15, 2019<br />
* Contact: Mark Dredze (mdredze@cs.jhu.edu)<br />
* Date posted: October 31, 2019<br />
* Website: https://www.cs.jhu.edu/about/employment-opportunities/<br />
<br />
http://apply.interfolio.com/69225<br />
<br />
The Johns Hopkins University’s Department of Computer Science seeks<br />
applicants for tenure-track faculty positions at all levels and across<br />
all areas of computer science. The department will consider offers in<br />
two tracks: (1) an open track seeking excellent candidates across all<br />
areas of computer science; and (2) a track seeking candidates in the<br />
areas of human computer interaction (HCI), human AI interaction,<br />
computational health, artificial intelligence and machine learning.<br />
The search will focus on candidates at the junior level, but all<br />
qualified applicants will be considered.<br />
<br />
Plans for faculty growth in the department are aligned with School and<br />
University initiatives in health and AI. Additionally, the faculty<br />
will continue to grow by adding excellent and diverse candidates<br />
across all areas of computer science. The HCI search is part of a<br />
newly-launched initiative (http://hci.jhu.edu) that seeks to transform<br />
existing HCI research activities across the university by making<br />
several faculty hires within Computer Science.<br />
<br />
The Department of Computer Science has 31 full-time tenured and<br />
tenure-track faculty members, 8 research and 5 teaching faculty<br />
members, 200 PhD students, 200 MSE/MSSI students, and over 500<br />
undergraduate students. There are several affiliated research centers<br />
and institutes including the Laboratory for Computational Sensing and<br />
Robotics (LCSR), the Center for Language and Speech Processing (CLSP),<br />
the JHU Information Security Institute (JHUISI), the Institute for<br />
Data Intensive Engineering and Science (IDIES), the Malone Center for<br />
Engineering in Healthcare (MCEH), the Institute for Assured Autonomy<br />
(IAA), and other labs and research groups. More information about the<br />
Department of Computer Science can be found at www.cs.jhu.edu and<br />
about the Whiting School of Engineering at<br />
https://engineering.jhu.edu.<br />
<br />
Applicants should submit a curriculum vitae, a research statement, a<br />
teaching statement, three recent publications, and complete contact<br />
information for at least three references.<br />
<br />
Applications must be made on-line at<br />
http://apply.interfolio.com/69225. While candidates who complete their<br />
applications by December 15, 2019 will receive full consideration, the<br />
department will consider applications submitted after that date.<br />
<br />
The Whiting School of Engineering and the Department of Computer<br />
Science are committed to building a diverse educational environment:<br />
https://www.cs.jhu.edu/diversity/.<br />
<br />
The Johns Hopkins University is committed to equal opportunity for its<br />
faculty, staff, and students. To that end, the University does not<br />
discriminate on the basis of sex, gender, marital status, pregnancy,<br />
race, color, ethnicity, national origin, age, disability, religion,<br />
sexual orientation, gender identity or expression, veteran status or<br />
other legally protected characteristic. The University is committed to<br />
providing qualified individuals access to all academic and employment<br />
programs, benefits and activities on the basis of demonstrated<br />
ability, performance and merit without regard to personal factors that<br />
are irrelevant to the program involved.<br />
<br />
<br />
<br />
== Assistant Professor with emphasis on Natural Language Processing, University of Georgia ==<br />
* Employer: Department of Computer Science, University of Georgia<br />
* Title: Assistant Professor<br />
* Speciality: NLP unspecified<br />
* Location: Athens, Georgia, USA<br />
* Deadline: November 13 2019<br />
* Contact: Krzysztof J. Kochut (kkochut@uga.edu)<br />
* Date posted: October 24th 2019<br />
<br />
Assistant Professor with emphasis on Natural Language Processing<br />
<br />
The Department of Computer Science at the University of Georgia invites applications for a tenure-track assistant professor position, starting August 2020. This position will complement and further strengthen our department’s research and education efforts in Natural Language Processing and offers a competitive salary and generous startup package. Applicants should hold a Ph.D. in Computer Science or related field.<br />
<br />
The ideal candidate for this position will have a strong research background in Natural Language Processing, and be committed to excellence in both research and teaching.<br />
<br />
Computer Science is a growing and congenial department of 35 faculty within the Franklin College of Arts and Sciences. The department has more than 1,150 undergraduate and more than 200 graduate students and offers the B.S., M.S., and Ph.D. degrees in CS. The teaching load allows for substantial concentration on research. In addition to the areas in which we are recruiting, our faculty cover a broad range of research interests, including algorithms, artificial intelligence, bioinformatics, brain imaging and mapping, computer security, computational science and high-performance computing, computer vision, data privacy, data science, distributed and real-time systems, machine learning, parallel and distributed computing, robotics, simulation, and semantic web. Please see http://www.cs.uga.edu for more information about the department and the university.<br />
<br />
The Franklin College of Arts and Sciences, its many units, and the University of Georgia are committed to increasing the diversity of its faculty and students, and sustaining a work and learning environment that is inclusive. Women, minorities, protected veterans and individuals with disability are encouraged to apply. The University of Georgia is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, ethnicity, age, genetic information, disability, gender identity, sexual orientation, or protected veteran status. Persons needing accommodations or assistance with the accessibility of materials related to this search are encouraged to contact Central HR (hrweb@uga.edu). Please do not contact the department or search committee with such requests. The University of Georgia (UGA), a land-grant and sea-grant university with statewide commitments and responsibilities is the state's oldest, most comprehensive and most diversified institution of higher education (http://www.uga.edu). UGA is currently ranked among the top 20 public universities in U.S. News & World Report. The University's main campus is located in Athens, approximately 65 miles northeast of Atlanta, with extended campuses in Atlanta, Griffin, Gwinnett, and Tifton. UGA was founded in 1785 by the Georgia General Assembly as the first state-chartered University in the country. UGA employs approximately 2,348 full-time faculty and more than 8,980 full-time staff. The University's enrollment exceeds 37,500 students including over 28,800 undergraduates and over 8,700 graduate and professional students. Academic programs reside in 17 schools and colleges, as well as a medical partnership with Augusta University housed on the UGA Health Sciences Campus in Athens.<br />
<br />
To apply, please go to http://www.ugajobsearch.com/postings/121338. Please upload a cover letter, curriculum vitae, and short statements of research interests and teaching philosophy. Please provide contact information (email and telephone number) for three references. Review of applications will begin on November 13, 2019 and will continue until the position is filled.<br />
<br />
== Assistant or Associate Professor, Dept. Information Systems and Cyber Security, University of Texas at San Antonio ==<br />
<br />
* Employer: The University of Texas at San Antonio<br />
* Title: Assistant or Associate Professor of Information Systems and Cyber Security<br />
* Specialty: NLP, text mining, machine learning, data science, or cyber security<br />
* Location: San Antonio, Texas, USA<br />
* Deadline: Open until filled<br />
* Date posted: 21 October 2019 <br />
* Contacts: Anthony Rios, (anthony.rios@utsa.edu)<br />
<br />
The University of Texas at San Antonio<br />
Department of Information Systems and Cyber Security<br />
<br />
The University of Texas at San Antonio Department of Information Systems and Cyber Security invites applicants for a tenure-track position (rank: Assistant or Associate) beginning Fall 2020.<br />
<br />
The position requires a Ph.D. degree in Information Systems, Cyber Security or related areas (e.g., Information Science, Computer Engineering, Computer Science, etc.) with a strong preference for a specialization in Data Analytics (e.g., machine learning, information retrieval, natural language processing, computational social science, etc.) or a specialization in Cyber Security. Candidates whose work lies at the intersection of Data Analytics and Cyber Security (e.g., anomaly detection in computing system data, artificial intelligence informed cyber situational awareness, etc.) are particularly encouraged to apply. Candidates must demonstrate strong potential for publishing in top-tier Information Systems, Data Analytics or Cyber Security publication venues. The successful candidate must demonstrate their ability to work with and be sensitive to the educational needs of diverse urban populations and support the university’s commitment to thrive as a Hispanic Serving Institution and a model for student success. Candidates will be expected to participate in departmental service activities. Candidates are also expected to participate in pursuing cross-disciplinary research grants. The ability to obtain and conduct federally-funded research that requires a top-secret security clearance is preferred. Responsibilities include research, teaching at the graduate and undergraduate levels and program development. The Department of Information Systems and Cyber Security consists of 14 tenured and tenure-track faculty members. Salary and benefits are competitive and commensurate with qualifications and experience. For additional information about the position, visit https://business.utsa.edu/faculty-and-research/faculty-openings/. <br />
<br />
Applicants must submit their full application package via the STARS program which is located at<br />
https://jobs.utsa.edu/.<br />
<br />
Applications will be accepted until the position is filled. Questions may be directed to Dr. Anthony Rios, chair of the search committee, at Anthony.Rios@utsa.edu. Tenured appointments are contingent upon Board of Regents approval. Applicants who are selected for interviews must be able to show proof that they will be eligible and qualified to work in the United States by time of hire. UTSA is an Affirmative Action/Equal Opportunity Employer. Women, minorities, veterans and individuals with disabilities are encouraged to apply.<br />
<br />
<br />
== Assistant Professor in Computational Linguistics, Dept. of Linguistics, University of Colorado at Boulder ==<br />
<br />
* Employer: University of Colorado<br />
* Title: Assistant Professor of Linguistics<br />
* Specialty: Computational Linguistics<br />
* Location: Boulder, Colorado, USA<br />
* Deadline: 1 November 2019<br />
* Date posted: 07 October 2019 <br />
* Contacts: Martha Palmer or Mans Hulden, (martha.palmer@colorado.edu) <br />
<br />
The Department of Linguistics at the University of Colorado Boulder seeks applications for an Assistant Professor tenure-track faculty position in Computational Linguistics beginning Fall 2020. Within Computational Linguistics we are particularly interested in candidates who use computational methods to address enduring questions in syntax, semantics and/or pragmatics, and other core areas of linguistics. We envision potential applications to Natural Language Processing and/or to discourse and dialogue advances that could be relevant to Human-Computer Interaction. Our primary consideration is the originality, intellectual breadth, and promise of the candidate’s work. This position will complement the strong, interdisciplinary cohort of Computational Linguistics faculty at CU and be affiliated with both our Center for Computational Language and EducAtion Research (CLEAR), and our cross-college Professional MS in Computational Linguistics, Analytics, Search and Informatics (CLASIC). The successful candidate will also benefit from our interdisciplinary partnerships with the Institute of Cognitive Science. We are especially interested in qualified candidates who can contribute, through their research, teaching, and service, to the diversity and excellence of our academic community.<br />
<br />
Full consideration will be given to applications that are completed by November 1, 2019. Applications will be accepted until February 15, 2020.<br />
<br />
For more details see:<br />
<br />
https://jobs.colorado.edu/jobs/JobDetail/?jobId=20950<br />
<br />
<br />
== Assistant Professor of Linguistics, Dept. of Linguistics, University of Kentucky ==<br />
<br />
* Employer: University of Kentucky<br />
* Title: Assistant Professor of Linguistics<br />
* Specialty: Computational Linguistics<br />
* Location: Lexington, Kentucky, USA<br />
* Deadline: 18 November 2019<br />
* Date posted: 07 October 2019 <br />
* Contacts: Mark Richard Lauersdorf (lauersdorf@uky.edu)<br />
<br />
The Department of Linguistics at the University of Kentucky in Lexington, Kentucky invites applications for a tenure track position at the rank of Assistant Professor of Linguistics to begin August 2020. The ideal candidate will have demonstrated research expertise using the tools and methodologies of computational linguistics in pursuit of theoretical linguistic questions, and an ability to teach courses in a range of computational and theoretical areas. We encourage candidates who apply computational methods in one or more of the following areas: syntax, semantics, phonology, phonetics, sociolinguistics, or historical linguistics. As a department and university, we are strongly committed to creating an inclusive and effective teaching, learning, research, and working environment for all.<br />
<br />
Responsibilities of the position include pursuing an active research program and teaching a total of four courses per year at the introductory, advanced undergraduate, and graduate levels. Responsibilities also include active participation in the academic life of the department, collaboration with units across campus (e.g., Computer Science, Modern and Classical Languages, Hispanic Studies), pursuing external funding, and providing service to the university and the discipline. Applicants are expected to have completed their PhD by August 2020.<br />
<br />
Interested applicants should apply online at: http://ukjobs.uky.edu/postings/251804. Applicants should submit the following: (1) letter of application, (2) current CV, (3) research statement (1-2 pages in which applicant describes current and future research agenda; upload as Specific Request 1), (4) a recent writing sample, (5) teaching statement (1-2 pages in which applicant discusses teaching philosophy and experiences; upload as Specific Request 2), and (6) a diversity statement (1-2 pages in which applicant reflects on commitments, approaches, and insights related to inclusion, diversity, and equity; upload as Specific Request 3). In addition, please provide the names and contact information for three references when prompted in the academic profile. This information may be utilized to solicit recommendation letters from your references within the employment system at a more advanced stage of the application process.<br />
<br />
All applications will be acknowledged. Deadline for the receipt of applications is November 18, 2019.<br />
<br />
For any questions relating to this position, please contact the chair of the search committee, Mark Richard Lauersdorf, at lauersdorf@uky.edu.<br />
<br />
The University of Kentucky is an Equal Opportunity Employer and encourages applications from veterans, individuals with disabilities, women, African Americans, and all minorities.<br />
<br />
<br />
== Postdoctoral Research Fellow on Sloan-sponsored NLP project, University of California, Berkeley ==<br />
<br />
* Employer: UC Berkeley<br />
* Title: Postdoctoral Fellow <br />
* Specialty: NLP, definition recognition, text equation analysis, information retrieval<br />
* Location: Berkeley, CA, USA<br />
* Deadline: Open until filled<br />
* Date posted: September 17, 2019 <br />
* Contacts: Marti Hearst (hearst@berkeley.edu)<br />
<br />
UC Berkeley’s School of Information and CS Division seeks a Postdoctoral Fellow to conduct research and algorithm development in Natural Language Processing, with a sub-interest in Information Retrieval or Citation Analysis. This position funds a researcher to work alongside Prof. Marti Hearst on a Sloan-funded project whose goal is to develop intelligent interfaces to the AI scientific literature, in collaboration with researchers and developers at AI2’s Semantic Scholar project. The Postdoctoral Fellow will develop novel algorithms and software to identify definitions within and between scientific papers in the co-citation network, analyze textual descriptions of mathematical notation, and other relevant NLP and IR research problems. This ambitious project provides an opportunity to test research results with tens of thousands of users in an open source environment. <br />
<br />
The Postdoctoral Fellow position requires a terminal degree appropriate to your discipline. The position does not have a teaching requirement, but if desired, the Fellow will have opportunities to teach and mentor both undergraduate and graduate students. The Fellow will be viewed as a colleague, and with mentorship, will be launched to the next career stage. <br />
<br />
Applicants should have experience conducting independent research, demonstrate a record of developing algorithms and supporting software, communicating research via publications and presentations, be excited about the goals of the project and about participating in collaborative, interdisciplinary research. Applicants must have defended their PhD in Computer Science, Information Science, or a related field by the time of employment.<br />
<br />
Applicants should have interests in one or more of the following areas: natural language processing, co-citation analysis, information retrieval. The ideal candidate is deeply interested in analyzing the text of documents via detecting and/or generating explanations and definitions within and between documents in a co-citation network. A background or interest in human computer interaction is a strong additional qualification. <br />
<br />
'''How do I apply?'''<br />
Interested candidates should prepare a single pdf file containing: (1) a cover letter stating background, experience, interest in the position, and career objectives, (2) a curriculum vitae or résumé, including a link to a web page with publications and other relevant information (3) the names and contact information for three references who can write a letter on your behalf, and (4) a relevant sample of published work. Send application materials to Prof. Marti Hearst (hearst@berkeley.edu) with the subject line: NLP postdoc application.<br />
<br />
'''How much does the position pay?''' <br />
The University classifies this as a Postdoctoral position. All recipients receive a salary of US $60,000/year for full-time employment as well as full benefits (https://vspa.berkeley.edu/postdoc-health-insurance-and-benefits). Additional funds are available for equipment and professional travel. <br />
<br />
'''When can I apply?''' <br />
Review of applications will begin on October 15, 2019 and will continue until the position is filled.<br />
<br />
'''When does the position start?''' <br />
January 2, 2020 is the preferred start date, although it can start earlier, but we can be flexible depending on other factors. The position will be for one year with possible extension for an additional half year.<br />
<br />
'''Will foreign applicants be considered?''' <br />
Yes. We highly encourage students from underrepresented groups to apply. UC Berkeley is an Equal Employment Opportunity (EEO) employer and welcomes all qualified applicants. Applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, veteran status, genetic data, or other legally protected status.<br />
<br />
<br />
<br />
<br />
== Research professor, Department of Computer Science, KU Leuven, Belgium == <br />
<br />
* Employer: KU Leuven <br />
* Title: Research professor<br />
* Specialty: Representation learning for natural language and multimedia processing<br />
* Location: Leuven, Belgium<br />
* Deadline: September 20, 2019 <br />
* Date posted: September 4, 2019 <br />
* Contact: Sien Moens (Sien.Moens@cs.kuleuven.be) <br />
<br />
The Department of Computer Science at KU Leuven has a full-time academic vacancy in the area in natural language and multimedia processing. The position is a research professorship with strongly reduced teaching responsibilities for the first 10 years. We seek applications from internationally oriented candidates with an outstanding research track record and excellent didactic skills. The successful candidate will perform research in the Human-Computer Interaction research group. The appointment is expected to start on October 1, 2020.<br />
<br />
More information is available at https://www.kuleuven.be/personeel/jobsite/jobs/55192105?hl=en&lang=en .<br />
<br />
== Postdoctoral researcher, KU Leuven, Belgium ==<br />
*Employer: Department of Computer Science, KU Leuven <br />
*Title: Postdoctoral researcher<br />
*Speciality: Representation learning in the context of natural language understanding<br />
*Location: Leuven, Belgium<br />
*Deadline: October 15, 2019<br />
*Date posted: September 4, 2019<br />
*Contact: sien.moens@cs.kuleuven.be<br />
<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The position focuses on natural language understanding but gives possibilities to research topics in one or more of the following fields: machine learning (especially semi-supervised learning, transfer learning, continual learning, deep learning and latent variable models), multimodal processing of language and visual data, learning the grounded meaning of language from various contexts in which language is used (e.g., physical, language and social), representation learning at the word, phrase, sentence or discourse level considering various contexts, learning commonsense knowledge about the world from multimodal data, multimodal grammar induction, and inference models for language understanding. The successful candidate will work on innovative natural language understanding research. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). <br />
<br />
<br />
<br />
== Postdoctoral fellow on IBM-sponsored NLP for human microbiome project, UC San Diego ==<br />
<br />
* Employer: UC San Diego<br />
* Title: Postdoctoral Fellow <br />
* Specialty: NLP, text mining, knowledge base construction<br />
* Location: La Jolla, CA, USA<br />
* Deadline: Open until filled<br />
* Date posted: August 22, 2019 <br />
* Contacts: Daniel Freed (CMIinfo@ucsd.edu)<br />
<br />
The automatic knowledge base construction group in the UC San Diego-IBM Artificial Intelligence for Healthy Living (AIHL) program, led by [https://profiles.ucsd.edu/chun-nan.hsu Dr. Chun-Nan Hsu] and [https://knightlab.ucsd.edu/wordpress/?page_id=47 Dr. Rob Knight], is seeking applications of a Postdoctoral Fellow in deep learning for natural language processing to extract microbiome knowledge from the scientific literature. The positions are available immediately. The project will be funded on a contract for three years. The research group is part of [https://cmi.ucsd.edu/ the Center for Microbiome Innovation (CMI)], one of the top research centers in the world in human microbiome research, developing AI, deep learning, and cutting edge data sciences to advance the understanding of the impact of microbiome to health. The knowledge base group has developed one of the most efficient and accurate algorithms in automated understanding of disease mentions in the scientific literature, winning [https://github.com/IBM/aihn-ucsd/tree/master/NormCo-deep-disease-normalization the Best Application Award in the 2019 conference of Automated Knowledge Base Construction (AKBC)]. Our former master student was admitted to prestigious PhD programs with fellowships.<br />
The group resides in the [http://qi.ucsd.edu/ Qualcomm Institute] (UC San Diego division of the California Institute for Telecommunications and Information Technology (Calit2)), the home of multidisciplinary research programs and startups at UCSD. The group has access to powerful GPU computer clouds at CMI and IBM. The group strives to deliver useful knowledge base systems and develop original, innovative, top-tier conference acceptable algorithms simultaneously. Group members work closely with CMI faculties and students and top-notch researchers from IBM in the Bay Area and around the world through frequent virtual and face-to-face meetings. The postdoctoral fellow will be encouraged to take initiation to explore new ideas to accomplish fully automatic knowledge base construction for human microbiome and work on grant proposals to develop into an independent leader of scientific research. <br />
<br />
'''Scope of research:'''<br />
* Learning from structured ontologies<br />
* Unsupervised, weakly supervised machine learning and active learning for NLP<br />
* Biomedical concept understanding<br />
* Event and relation extraction and inference<br />
'''Qualifications:'''<br />
* Ph.D. in a relevant discipline, including in the areas of natural language processing, machine learning, or bioinformatics and systems biology<br />
* Strong record in publications in top-tier AI conferences and Bioinformatics journals<br />
* Undergraduate or graduate coursework or degree in Biology or a related field is a plus<br />
<br />
'''How to Apply:'''<br />
Please email a completed application form (http://cmi.ucsd.edu/PostDocApplication) and support documents to CMIInfo@ucsd.edu to apply.<br />
<br />
''Note: If you have relatives employed at UC San Diego, you must include the name, relationship and department where employed in your resume or cover letter. This information is used only for the purpose of complying with the University’s nepotism policy.<br />
''<br />
<br />
== Postdocs on Facebook-sponsored neural NLG project, Ohio State University ==<br />
<br />
* Employer: The Ohio State University<br />
* Title: Postdoctoral Scholar <br />
* Specialty: NLG, conversational systems, NLP<br />
* Location: Columbus, OH, USA<br />
* Deadline: August 18, 2019<br />
* Date posted: August 2, 2019 <br />
* Contacts: Michael White (mwhite@ling.osu.edu)<br />
<br />
Multiple postdoctoral scholar positions are open at Ohio State for a Facebook-sponsored project on natural language generation in conversational system with the theme of structure in neural NLG. <br />
<br />
Full details are available on the application page: https://www.jobsatosu.com/postings/96937<br />
<br />
== Open Rank Professor, iSchool and Department of Criminology and Criminal Justice, University of Maryland == <br />
<br />
* Employer: University of Maryland <br />
* Title: Open Rank Professor <br />
* Specialty: Data-driven analyses in crime, law and justice <br />
* Location: College Park, MD<br />
* Deadline: October 1, 2019 (deadline for full consideration, late applications may be accepted)<br />
* Date posted: July 26, 2019 <br />
* Contacts: Katie Shilton (kshilton@umd.edu) and Laura Dugan (ldugan@umd.edu)<br />
<br />
The College of Information Studies (Maryland’s iSchool) and the Department of Criminology and Criminal Justice at the University of Maryland, College Park invite applications for an open rank tenure-track or tenured faculty position with a focus on building systems for and conducting data-driven analyses in crime, law and justice. Examples of possible research approaches include: data mining; information visualization; automating or advancing data pre-processing; signal processing, computer vision, and natural language processing; applied machine learning; algorithmic transparency, debiasing algorithms and data, and algorithmic accountability; and computational<br />
social science.<br />
<br />
We are interested in candidates who apply these topics in the context of criminology, justice, and criminal law (e.g., predictive policing, pretrial risk assessment, database building through open sources, linking criminal records, recidivism prediction, management of bodycam video, face recognition in surveillance images, management of DNA evidence). Candidates with data-driven approaches to related social science topics are encouraged to apply.<br />
<br />
Applicants should apply electronically at https://ejobs.umd.edu/postings/71777.<br />
<br />
== Tenure-track Assistant Professor of Computational Linguistics, Boston University == <br />
<br />
* Employer: Boston University<br />
* Title: Assistant Professor <br />
* Specialty: Computational Linguistics<br />
* Location: Boston, MA<br />
* Deadline: October 20, 2019 (deadline for full consideration, late applications may be accepted)<br />
* Date posted: July 24, 2019 <br />
* Contact: Carol Neidle <carol@bu.edu> <br />
<br />
The Boston University Linguistics Department seeks a tenure-track Assistant Professor of Computational Linguistics (for primary appointment in Linguistics, secondary appointment in or affiliation with Computer Science), beginning July 1, 2020, pending budgetary approval; to conduct research, teach courses in Computational Linguistics and related areas (Linguistics, Computer Science) at introductory and advanced levels, and advise graduate and undergraduate students. Should have excellent programming skills and experience in computational linguistic research. Experience in application of computational methods to field linguistics or analysis of understudied languages would be a plus. Requirements include PhD in Linguistics (preferred) or Computer Science in hand by start date, with strong background in both fields, and demonstrated excellence in teaching, advising, and research. For further information: http://ling.bu.edu/ and http://www.bu.edu/cs/ .<br />
<br />
Applications should be uploaded through https://academicjobsonline.org/ajo/jobs/14064. Full details of application requirements, as well as a statement of the university’s commitment to diversity and inclusion, are available on that site.<br />
<br />
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We are a VEVRAA Federal Contractor.<br />
<br />
<br />
== Full-Time Research Engineer, New York University == <br />
<br />
* Employer: New York University<br />
* Title: Research Engineer<br />
* Specialty: Open-source software, pretraining and transfer learning<br />
* Location: New York, USA<br />
* Deadline: July 31, 2019 (deadline for full consideration, late applications may be accepted)<br />
* Date posted: July 17, 2019 <br />
* Contact: Sam Bowman <bowman@nyu.edu> <br />
<br />
'm hiring a full-time research engineer. If you're interested in transitioning from software engineering to NLP/ML research, and you'd be up for a stint in an academic lab, there's more information and an application from here: https://apply.interfolio.com/65666 <br />
<br />
== PhD in Biomedical Information Extraction, The University of Manchester, UK == <br />
<br />
* Employer: University of Manchester<br />
* Title: PhD in Biomedical Information Extraction<br />
* Specialty: Natural Language Processing, Text Mining, Machine Learning<br />
* Location: Manchester, UK<br />
* Deadline: May 26, 2019 <br />
* Date posted: May 10, 2019 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk), School of Computer Science in collaboration with the Faculty of Biology, Medicine and Health, The University of Manchester, offer a PhD scholarship to advance research in neural information extraction applied to cancer mechanisms. <br />
<br />
Candidates must have a minimum upper second class first degree in Computer Science and an MSc in Computer Science or a related discipline. Experience in machine learning and neural networks applied to NLP are highly desirable, as is the ability to work in an interdisciplinary setting.<br />
<br />
Further information can be obtained here: http://nactem.ac.uk/newsitem.php?item=393<br />
<br />
== PhD in Biomedical Information Extraction, The University of Manchester, UK == <br />
<br />
* Employer: University of Manchester<br />
* Title: PhD in Biomedical Information Extraction<br />
* Specialty: Natural Language Processing, Text Mining, Machine Learning<br />
* Location: Manchester, UK<br />
* Deadline: May 26, 2019 <br />
* Date posted: May 10, 2019 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk), School of Computer Science in collaboration with the Faculty of Biology, Medicine and Health, The University of Manchester, offer a PhD scholarship to advance research in neural information extraction applied to cancer mechanisms. <br />
<br />
Candidates must have a minimum upper second class first degree in Computer Science and an MSc in Computer Science or a related discipline. Experience in machine learning and neural networks applied to NLP are highly desirable, as is the ability to work in an interdisciplinary setting.<br />
<br />
Further information can be obtained here: http://nactem.ac.uk/newsitem.php?item=393<br />
<br />
<br />
== 24-month Postdoctoral Position, IRISA (France, Lannion), Paraphrase Generation / Natural Language Generation ==<br />
<br />
* Employer: [https://www.univ-rennes1.fr/ University of Rennes 1]<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Natural language processing<br />
* Duration: 24 months<br />
* Location: Lannion, France<br />
* Deadline: until filled<br />
* Date posted: April 23, 2019<br />
* Contact: Gwénolé Lecorvé (gwenole.lecorve@irisa.fr), Jonathan Chevelu (jonathan.chevelu@irisa.fr)<br />
<br />
'''Overview'''<br />
<br />
IRISA [https://www.irisa.fr/] is the largest research laboratory dedicated to computer science in France, hosting more than 800 people and 40 research teams. Its activities spans all the fields of computer science. It is located in Rennes, Lannion, and Vannes.<br />
<br />
The Expression team [https://www-expression.irisa.fr/] works on natural language processing (NLP), be it through texts, speech or gestures. In particular, it focuses on the expressive components of the human languages.<br />
<br />
The opened position is part of the ANR TREMoLo project [http://tremolo.irisa.fr] hosted by the team and aimed at transforming the language register of texts, for instance mapping a text from the formal register to the casual one. This involves work on linguistic characterization, pattern mining and paraphrase generation. The activities are conducted on the French language.<br />
<br />
The recruited person will work on a paraphase generation and propose solution to integrate register-specific stylistic constraints. She/he is expected to investigate on the use of statistical and neural paraphrasing systems, that is:<br />
* Training of a baseline systems using either statistical or neural approaches.<br />
* Intregration of constraints formulated as sequential patterns.<br />
* Organization of evaluation campaigns.<br />
<br />
'''Job requirements'''<br />
<br />
* PhD in natural language processing or machine learning<br />
* Top academic and publication records<br />
* Good communication skills<br />
* Team work experience<br />
* Knowledge in French is a plus but is not required.<br />
<br />
== Postdoctoral Position Available in Natural Language Processing and Human-Robot Interaction, Army Research Lab ==<br />
<br />
* Employer: [https://www.orau.org/arlfellowship/ US Army Research Laboratory]<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Natural language processing, human-robot interaction, dialogue systems<br />
* Location: Adelphi, Maryland, United States with ~8 weeks of travel per year to Boston<br />
* Deadline: April 30, 2019 (or until filled)<br />
* Date posted: April 15, 2019<br />
* Contact: Matthew Marge (matthew.r.marge.civ@mail.mil)<br />
<br />
'''Overview'''<br />
<br />
The [https://www.arl.army.mil US Army Research Laboratory] (ARL) is welcoming applications for a one-year renewable (up to 3 years) postdoctoral position at the intersection of natural language processing (NLP) and human-robot interaction (HRI), focusing on dialogue with robots. The successful candidate will contribute to the research and development of the project, “Learning about the Physical World Autonomously through Information-Theoretic Dialogue”, funded by the Office of the Secretary of Defense's Laboratory University Collaboration Initiative (LUCI) Fellowship. The goal of the project is to investigate techniques for robots to learn, from natural language dialogue, about objects and actions in the physical world. <br />
<br />
In support of this effort, ARL is looking for an individual with a PhD or equivalent experience, with interest and a background in human-robot interaction, natural language processing, symbol grounding, and/or dialogue systems. We plan to develop an approach to detecting uncertainty about objects and actions using multiple modalities (e.g., language and vision), so that robots can initiate natural language questions that humans can answer that maximize the agent's information gain in a situation. <br />
<br />
The project is supervised by Dr. Matthew Marge (ARL), with co-PI Dr. Gordon Briggs (NRL), and faculty collaborator Prof. Matthias Scheutz (Tufts University). The successful candidate will collaborate with the PIs on designing human-robot interaction experiments and developing techniques to support human-robot dialogue systems. <br />
<br />
The position is available immediately with a duty station at the Adelphi Laboratory Center (ALC), Adelphi, MD (Washington, D.C. metro area), with extended travel (~8 weeks per year) to Boston, MA to visit the Human-Robot Interaction Lab at Tufts University and periodic travel to the Laboratory for Autonomous Systems Research at the Naval Research Laboratory, Washington, D.C. <br />
<br />
'''Job requirements:'''<br />
* Ph.D. or equivalent research experience in computer science, artificial intelligence, computational linguistics, human-robot interaction, computer engineering or related field.<br />
* U.S. citizenship is preferred.<br />
<br />
To learn more about this position, or to apply, please send questions or a CV to Dr. Matthew Marge at matthew.r.marge.civ@mail.mil. <br />
<br />
== Associate Research Scientist in Natural Language Processing, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ukp/ukp_home/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural Language Generation, Semantics and Discourse Processing, Multi-document Information Consolidation<br />
* Location: Darmstadt<br />
* Deadline: April 30, 2019 (or until filled)<br />
* Date posted: April 12, 2019<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ukp/ukp_home/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD-level; for an initial term of two years)'''<br />
<br />
This position should further strengthen the group’s profile in one or more areas of Natural Language Processing (NLP), such as natural language generation, semantics and discourse processing, or multi-document information consolidation. <br />
<br />
UKP Lab is a research group comprising over 30 team members who work on various aspects of data-driven NLP and machine learning with their novel applications in various domains, e.g. conversational IR systems, scientific literature analysis, or social media mining.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Natural Language Processing or Text Mining, preferably with prior expertise in the relevant areas of computer science and strong programming skills. Experience with neural network architectures and demonstrable engagement in open source projects are strong advantages. Strong communication skills in English are a must. <br />
<br />
UKP’s provides an excellent cooperation network with both top academic and industrial partners in Artificial Intelligence (AI), and a supportive research environment within the lab. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique profile around AI and the DFG-funded Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) emphasize NLP, machine learning, and scalable infrastructures for the assessment and aggregation of information. UKP Lab is a high-profile research group committed to cutting-edge research, dynamic operations, cooperative work style and close interaction of team members. The selected candidates will have an opportunity for professional growth according to their seniority level. <br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous work or research experience (if available).<br />
Applications from women are particularly encouraged. <br />
All other things being equal, candidates with disabilities will be given preference. <br />
<br />
Please submit your application via the following form by April 30th, 2019: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. <br />
The position is open until filled.<br />
<br />
== Senior Research Scientist - Natural Language Processing at Bosch Research == <br />
<br />
* Employer: Bosch Research<br />
* Title: Senior Research Scientist (Principal level position also available)<br />
* Specialties: Natural language processing, natural language understanding, information retrieval, question answering, information extraction.<br />
* Location: Sunnyvale, CA, USA<br />
* Deadline: N/A (The position is open until filled)<br />
* Date Posted: March 7, 2019 <br />
* Website: http://smrtr.io/_cXw <br />
<br />
'''Company Description'''<br />
<br />
The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human Machine Interaction (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design. In all areas we work in close collaboration with our partners at leading US universities, leading-edge industry partners, and other worldwide Bosch research, development, and marketing units.<br />
<br />
The focus of our global HMI research includes Visual Computing, Audio and Language Computing, Conversational AI, Smart Wearables and Haptics, User Experience (UX) and Human Factors, etc. We develop intuitive, interactive and intelligent solutions to enable an inspiring UX for Bosch products and services in application areas such as autonomous driving, car infotainment and driver assistance systems (ADAS), Industry 4.0 and Internet of Things (IoT), security systems, smart home and building solutions, health care, and robotics.<br />
<br />
As a part of the global Human Machine Interaction research unit, our Language and Audio Computing group is responsible for shaping the future user experience of Bosch products by developing cutting-edge technologies and prototype systems in the fields of text and audio processing, including natural language processing, natural language understanding, question answering, information retrieval, and audio signal processing. We work on solutions to hard challenges of truly understanding the human language and audio signals, extracting the semantics from text and audio, and enabling natural, intuitive and intelligent HMI and personal assistance. We work with internal partners at various Bosch business units to transfer our ideas and solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals, e.g., ACL, EMNLP, NAACL, COLING, AAAI, ISWC, Interspeech, ICASSP<br />
<br />
'''Job Description'''<br />
<br />
* Drive advanced research and engineering of Natural Language Processing (NLP) technologies<br />
* Apply research results to Bosch prototypes, products and services of information retrieval, question answering, conversational AI, and information extraction.<br />
* Working together with Bosch business units to integrate the resulting system/software into Bosch platform with high quality implementation<br />
* Summarize research findings in high-quality paper and/or patent submissions<br />
<br />
== Natural Language Processing Research Associate (KTP Associate) in Wilmslow, Cheshire, UK == <br />
<br />
* Employer: University of Manchester<br />
* Title: Natural Language Processing Research Associate (KTP Associate)<br />
* Specialty: Natural Language Processing, Text Mining, Machine Learning<br />
* Location: Wilmslow, Cheshire, UK<br />
* Deadline: April 7, 2019 <br />
* Date posted: March 7, 2019 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
An exciting opportunity has arisen for an ambitious graduate who has the ability and confidence to undertake a Knowledge Transfer Partnership (KTP) project between the National Centre for Text Mining (NaCTeM), University of Manchester and Bott and Co. <br />
<br />
Bott and Co is a multiple award-winning solicitors based in Wilmslow, near Manchester, with particular expertise in flight delay compensation, holiday sickness and road traffic accident claims.<br />
<br />
The successful KTP associate will work with supervisors from both NaCTeM and Bott on a 30 month project, which has the overall aim of building a state-of-the-art Natural Language Processing (NLP) system for legal text mining and predictive modelling (PM).<br />
<br />
The position will provide you with a unique opportunity to apply state-of-the-art methods in NLP and PM in the scope of legal analysis.<br />
<br />
This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and industry. <br />
<br />
<br />
ESSENTIAL SKILLS<br />
<br />
* BSc and MSc degree in Computer Science or related areas<br />
* Specialist (PhD-level) knowledge in Natural Language Processing or extensive experience in the development of NLP/text analysis software<br />
* Experience in use of deep learning for NLP/text mining<br />
* Experience of machine learning (especially of context aware linear models for multi-task learning, and of active learning) for NLP/text mining<br />
* Experience of probabilistic inference, predictive modelling and decision making<br />
* Software development experience in Java or Python<br />
<br />
<br />
LOCATION - Bott and Co, Wilmslow, Cheshire <br />
<br />
SALARY - £32,236 to £39,609 per annum plus performance bonus and £5,000 personal development budget<br />
<br />
DURATION - 30 months - starting ASAP <br />
<br />
CLOSING DATE - 07/04/2019<br />
<br />
FURTHER DETAILS AND APPLICATION FORM - https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16973<br />
<br />
<br />
== Postdoc position, KU Leuven ==<br />
*Employer: Department of Computer Science, KU Leuven <br />
*Title: Postdoctoral Researcher<br />
*Speciality: Representation learning in the context of natural language understanding<br />
*Location: Leuven, Belgium<br />
*Deadline: February 28, 2019<br />
*Date posted: February 13, 2019<br />
*Contact: sien.moens@cs.kuleuven.be<br />
<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The position focuses on natural language understanding but gives possibilities to research topics in one or more of the following fields: machine learning (especially semi-supervised learning, transfer learning, incremental learning, deep learning and latent variable models), multimodal processing of language and visual data, learning the grounded meaning of language from various contexts in which language is used (e.g., physical, language and social), representation learning at the word, phrase, sentence or discourse level considering various contexts, learning commonsense knowledge about the world from multimodal data, multimodal grammar induction, and inference models for language understanding. The successful candidate will work on innovative natural language understanding research. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship. <br />
<br />
<br />
KU Leuven ranks among the top 50 universities in THE World University Rankings 2019. The alumni of the LIIR lab have obtained outstanding positions in academics and industry (see https://liir.cs.kuleuven.be/people.php).<br />
<br />
<br />
'''Responsibilities'''<br />
<br />
*Perform research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.<br />
*Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor and master theses.<br />
*Help in the supervision of PhD researchers of the CALCULUS team.<br />
<br />
'''Profile'''<br />
<br />
*You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
*You have a motivated interest in fundamental research in language understanding and machine learning. <br />
*You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.<br />
*You are good at collaborating with and leading others.<br />
*You have a very good knowledge of English, both spoken and written.<br />
<br />
<br />
'''Offer'''<br />
<br />
*We offer a 2 x two-year postdoctoral position, starting in the summer of 2019.<br />
*We offer a competitive wage and yearly budget to attend conferences and for short research stays.<br />
<br />
'''Interested'''<br />
<br />
Please contact Prof. dr. Marie-Francine Moens, tel.: +32 16 32 53 83, mail: sien.moens@kuleuven.be.<br />
Excellent candidates will be invited for an interview (possibly via Skype). The position will be closed when a valuable candidate is found.<br />
<br />
<br />
<br />
== Postdoc position, Masaryk University ==<br />
*Employer: Machine Learning and Data Processing Department, Faculty of Informatics, Masaryk University<br />
*Title: Postdoctoral Researcher<br />
*Speciality: natural language processing, knowledge representation and reasoning<br />
*Location: Brno, Czech Republic<br />
*Deadline: March 1, 2019<br />
*Date posted: January 15, 2019<br />
*Contact: Ales Horak: hales@fi.muni.cz, subject "Postdoc 2019"<br />
*Application link: https://www.muni.cz/en/about-us/careers/vacancies/43809<br />
<br />
The Faculty of Informatics of Masaryk University (FI MU) in Brno, Czech Republic, invites applications for Post-doctoral positions in all areas of Computer Science. Brno, the second largest city in the Czech Republic, see https://www.gotobrno.cz/en/, is an attractive city for students and young researchers. The Faculty has a strong interest in attracting applications from abroad.<br />
<br />
The postdoctoral positions are awarded for one year with an extension to the second year after a review. Gross salary is 50,000 CZK per month which, with an optional 10% bonus, sums to more than 25,500 EUR per year. Additional funds of 4,000 EUR per year will be available for travel and material expenses. Preferred start date of the contract is in June/July 2019, but other options can be negotiated without hassle.<br />
<br />
'''Requirements'''<br />
<br />
Candidates must have a PhD degree not older than 4 years at the time of application, from a university outside of the Czech and Slovak Republics. In case that the PhD defense is not yet finished, the candidate must also provide an official letter certifying that his/her PhD thesis has already been submitted for defense and outlining the expected schedule of the PhD defense. Candidates with a PhD degree from a Czech or Slovak university may also be considered if they prove at least two years of post-doctoral research experience abroad.<br />
<br />
'''Evaluation'''<br />
<br />
All candidates are expected to be fluent in English, while prior knowledge of Czech is not required. Candidates will be evaluated on the ground of their strong international research record, and preference will be given to those whose research areas match the research directions of the Faculty of Informatics; see http://www.fi.muni.cz/research/.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted electronically at the attached www address - the electronic application form (only reference letters, if not given directly to the applicant, may be sent by email). The applicants should provide the following documents with their application:<br />
*An academic CV, a list of publications, and a motivation letter.<br />
*A scanned copy of the PhD diploma, or a letter certifying submission of doctoral thesis for the defense.<br />
*One external reference letter, and one support letter (expression of interest) from a member of the academic staff of the Faculty of Informatics of Masaryk University. These letters, if cannot be attached by the applicant him/herself, may be sent to the e-mail address hales@fi.muni.cz.<br />
<br />
All interested applicants are strongly advised to informally contact their expected host research groups at the Faculty of Informatics well ahead of submitting their application.<br />
<br />
'''Contact'''<br />
<br />
Assoc.Prof. Ales Horak, Head of the Department of Machine Learning and Data Processing<br />
<br />
Submission of applications: https://www.muni.cz/en/about-us/careers/vacancies/43809<br />
<br />
E-mail (for inquiries and reference letters): hales@fi.muni.cz, subject "Postdoc 2019"</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities_posted_2018&diff=12886Employment opportunities posted 20182020-06-02T12:02:31Z<p>Tristan Miller: Archived from Employment opportunities, postdoctoral positions, summer jobs</p>
<hr />
<div>* This is an archive of employment opportunities that were posted in 2018.<br />
<br />
== Two postdoctoral positions, University of Pittsburgh ==<br />
*Employer: The Computational Social Dynamic Lab, University of Pittsburgh<br />
*Title: Postdoctoral Research Associate<br />
*Speciality: computational social science, NLP, machine learning.<br />
*Location: Pittsburgh, PA, USA<br />
*Deadline: January 15, or until position filled<br />
*Date posted: December 06, 2018<br />
*Contact: Yu-Ru Lin (email: <yuruliny@gmail.com> | web: http://yurulin.com | lab: https://picsolab.github.io/)<br />
<br />
The Computational Social Dynamic (PICSO) Lab at the University of Pittsburgh is seeking two postdoctoral research associates for a computational social science project under the mentorship of Dr. Yu-Ru Lin and Dr. Rebecca Hwa. This highly interdisciplinary project aims to advance research methodology in revealing biases of different groups or cultures by analyzing social media data with cutting-edge methods of natural language processing and machine learning. The duration of the position is for one year, with the possibility of renewal. The compensation is competitive. <br />
<br />
We welcome candidates who hold a PhD from a related background, including computational social science, computer science, computational linguistics, social psychology, sociology, political science, and applied mathematics. Particular priorities for hiring are: (1) knowledge and experiences in distributed semantic representation, sentiment analysis, and text mining methods, ideally demonstrated by publications in established venues (ACL, EMNLP, NIPS, ICML, KDD, etc.); (2) demonstrated ability to work with social media data; (3) prior experiences with computational social sciences a plus.<br />
<br />
For full consideration, candidates should submit the following materials electronically '''''as a single PDF file''''' to Dr. Yu-Ru Lin at <yuruliny@gmail.com>:<br />
# A brief statement of interest describing your relevant background<br />
# Current CV<br />
# The names and contact information for two references (letters of recommendation will be solicited from finalists)<br />
# Two publications or other writing samples<br />
Please include "PostDoc Application 2019" in the email subject line. <br />
<br />
== Research Scientist Interns at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Systems Incorporated<br />
*Title: Research Scientist Intern <br />
*Speciality: NLP, machine learning, dialog, and question answering.<br />
*Location: San Jose, CA, USA<br />
*Deadline: March 1, 2019<br />
*Date posted: December 06, 2018<br />
*Contact: bui@adobe.com<br />
<br />
We are looking for Master and/or Ph.D. students with a strong background in NLP, machine learning, dialog, and/or question answering to work on our Creative Assistant project and Document Question Answering project. See our recent publications here for further details: https://sites.google.com/site/trungbuistanford/Home/publications<br />
<br />
== Assistant Professor Position at The University of Memphis ==<br />
<br />
* Employer: University of Memphis<br />
* Rank or Title: Assistant Professor<br />
* Specialty: ML/NLP with particular interest in educational technologies<br />
* Location: Memphis, Tennessee<br />
* Deadline: 1/7/19 but applications accepted until search completed<br />
* Date Posted: 11/28/18<br />
* Contact email: cconnor2@memphis.edu<br />
* Application link: [https://workforum.memphis.edu/postings/20504]<br />
<br />
The Department of Computer Science at the University of Memphis is seeking candidates for an Assistant Professor position beginning Fall 2019. The candidate’s research will be jointly supported by the Department of Computer Science and the Institute of Intelligent Systems (IIS). Focus area for this position include Machine Learning, Data Mining, and Big Data. Candidates whose research areas complement the language & discourse or learning focus area of the IIS are particularly encouraged to apply. Candidates from minority and underrepresented groups are highly encouraged to apply. Successful candidates are expected to develop externally sponsored interdisciplinary research programs, teach both undergraduate and graduate courses and provide academic advising to students at all levels. <br />
<br />
Applicants should hold a PhD in Computer Science, or related discipline, and be committed to excellence in both research and teaching. Salary is highly competitive and dependent upon qualifications. <br />
<br />
The Department of Computer Science ([http://www.cs.memphis.edu]) offers B.S., M.S., and Ph.D. programs as well as graduate certificates in Data Science and Information Assurance, and participates in an M.S. program in Bioinformatics (through the College of Arts and Sciences). The Department has been ranked 55th among CS departments with federally funded research. The Department regularly engages in large-scale multi-university collaborations across the nation. For example, CS faculty led the NIH-funded Big Data "Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K)" and the "Center for Information Assurance (CfIA)". <br />
<br />
The Institute for Intelligent Systems consists of 54 faculty members across 14 departments including Communication Sciences and Disorders, Computer Science, Engineering, Education, Linguistics, Philosophy and Psychology. The IIS offers a graduate certificate in Cognitive Science, a minor in Cognitive Science, and is affiliated with BA and MS programs in other departments. The IIS receives $4-5 million in external awards per year from federal agencies such as NSF, IES, DoD, and NIH. Further information about the Institute for Intelligent Systems can be found at [http://iis.memphis.edu].<br />
<br />
Known as America’s distribution hub, Memphis ranked as America’s 6th best city for jobs by Glassdoor in 2017. Memphis metropolitan area has a population of 1.3 million. It boasts a vibrant culture and has a pleasant climate with an average temperature of 63 degrees. <br />
<br />
Screening of applications begins immediately. For full consideration, application materials should be received by January 7, 2019. However, applications will be accepted until the search is completed. <br />
<br />
To apply, please visit [https://workforum.memphis.edu/postings/20504]. Include a cover letter (please include a reference to this position as “CS-IIS”), curriculum vitae, statement of teaching philosophy, research statement, and three letters of recommendation. Direct all inquiries to Corinne O’Connor (cconnor2@memphis.edu). <br />
<br />
A background check will be required for employment. The University of Memphis is an Equal Opportunity/Equal Access/Affirmative Action employer committed to achieving a diverse workforce.<br />
<br />
== Research Associate in Text Mining, University of Manchester, UK == <br />
<br />
* Employer: University of Manchester<br />
* Title: Research Associate in Text Mining<br />
* Specialty: Text Mining<br />
* Location: Manchester, UK<br />
* Deadline: January 3, 2019 <br />
* Date posted: November 27, 2018 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
We invite applications for the Research Associate in Text Mining, which is tenable initially for 12 months starting as soon as possible. The post is part of the Discovering Safety Programme funded by Lloyds Register Foundation in collaboration with the Health and Safety Executive. The purpose of this project is to use a combination of text mining and machine learning methods for retrieving and organising textual information pertinent to incident and inspection reports for search and risk classification.<br />
<br />
Post Objectives:<br />
<br />
1. To develop a search system based on clustering methods.<br />
<br />
2. To contribute to development of entity linking for the application.<br />
<br />
3. To develop a classification system for risk assessment.<br />
<br />
You should have a PhD or equivalent in Computer Science with emphasis in Text Mining and Machine Learning in particular clustering and classification. Experience in named-entity recognition, entity linking and terminology extraction will be desirable. Appropriate security clearance may be required for the successful applicant.<br />
<br />
* Salary : £32,236 - £39,609 per annum according to experienc<br />
* Hours Per week: Full Time<br />
* Contract Duration : 01 February 2019 until 31 January 2020<br />
<br />
Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16445<br />
<br />
== Research Fellow in Natural Language Processing and Text Mining, University of Manchester, UK == <br />
<br />
* Employer: University of Manchester<br />
* Title: Research Fellow in Natural Language Processing and Text Mining<br />
* Specialty: Text Mining<br />
* Location: Manchester, UK<br />
* Deadline: January 3, 2019 <br />
* Date posted: November 23, 2018 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
We invite applications for the above position to increase the University of Manchester's capacity in Natural Language Processing and Text Mining, which is available immediately for an initial 5 year period leading to an open-ended academic position.<br />
<br />
The Research Fellow will further strengthen the research profile of the text mining research group at the University of Manchester and the National Centre for Text Mining. We are looking for an outstanding candidate that has a vision for making a significant impact on natural language processing, text mining research and its applications. The Fellow will be part of the Discovering Safety Programme project funded by Lloyds Register Foundation in collaboration with the Health and Safety Executive. This post is one of the key first posts to be appointed in the Thomas Ashton Institute for Risk and Regulatory Research.<br />
<br />
You will join the vibrant research environment of the Text Mining research group at the School of Computer Science and will be a member of the National Centre for Text Mining which is developing cross cutting and innovative approaches for text mining applications using NLP and machine learning.<br />
<br />
As a member of the Thomas Ashton Institute, the Fellow will join, and help establish, a multidisciplinary centre of excellence and expertise, which offers an exciting opportunity for ground breaking and excellent research to inform both government regulatory regimes and industry practice. <br />
<br />
* Salary : £40,792 to £50,132 per annum dependent upon experience<br />
* Hours Per week: Full Time<br />
* Contract Duration : Starting Immediately until 31 December 2023<br />
<br />
Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16448<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Text Analysis and Natural Language Processing Tools<br />
* Location: Darmstadt<br />
* Deadline: December 15, 2018 (or until filled)<br />
* Date posted: November 22, 2018<br />
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of ''Interactive Text Analysis'' and ''Natural Language Processing Tools''. The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of ''Natural Language Processing'' (NLP), with a rapidly developing focus on Interactive Machine Learning. Besides, we provide a range of high-quality open source software packages for interactive and automatic text analysis to research and industry communities and collaborate with both academic and industrial partners.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Semantic Web Technologies and either Information Retrieval or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German.<br />
<br />
The successful applicant will work on research and development for interactive text annotation by end-users (researchers, analysts, etc.). This includes neural network-based methods for knowledge graph construction and completion, interactive sequence labeling recommender systems, or semantic information retrieval. We integrate the results in a real-life collaborative text annotation software for large-scale interactive corpus analysis.<br />
<br />
Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems (frontend and backend), in applying NLP-related Machine Learning-based methods (e.g. learning-to-rank, clustering, etc.), experience with information retrieval systems (e.g. Lucene, Solr, ElasticSearch) and relational databases (SQL), semantic web technologies (e.g. RDF, OWL, SPARQL), and strong programming skills especially in Java. Experience with neural network architectures (e.g. knowledge-base embeddings) and demonstrable engagement in open- source projects are a strong plus.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: December 15, 2018 (or until filled)<br />
* Date posted: November 22, 2018<br />
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD- or (Senior-)PostDoc level; for an initial term of two years)'''<br />
<br />
The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of ''Natural Language Processing'' (NLP), with an emphasis on semantic text analysis and generation, argument mining, and interactive machine learning. Besides, we have a strong profile in deep learning for NLP, construction of large-scale benchmarks, or knowledge graphs. We collaborate with a wide range of both academic and industrial partners.<br />
<br />
We are looking for candidates in Computer Science with a specialization in Natural Language Processing, preferably with expertise in research and development projects, prior publication experience, and strong communication skills. The research topics of the position may include: NLP in low-research settings, argument mining and retrieval, multimodal content processing, privacy-enhanced NLP as well as machine learning for NLP (deep reinforcement learning, neural network architectures). The successful applicant will work on research and development as part of a team in one of the areas above. We disseminate the results in top venues of the field and as free research software and datasets. The lab offers highly attractive options for personal growth and career development at all levels of the scientific career. Upon interest, additional qualifications in teaching and project management can be acquired.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Assistant Professor, Department of Linguistics and Translation, University of Montreal == <br />
<br />
* Employer: Department of Linguistics and Translation, University of Montreal<br />
* Title: Assistant Professor (tenure-track)<br />
* Specialty: Computational linguistics<br />
* Location: Montreal, Canada<br />
* Deadline: December 13, 2018 <br />
* Date posted: November 10, 2018 <br />
* Contact: Mireille Tremblay <mireille.tremblay.4@umontreal.ca > and https://ling-trad.umontreal.ca<br />
<br />
The Département de linguistique et de traduction is seeking applications for a full-time tenure-track position at the rank of Assistant Professor in computational linguistics/natural language processing.<br />
<br />
Responsibilities<br />
<br />
The appointed candidate will be expected to teach at all three levels of the curriculum, supervise graduate students, engage in ongoing research and publication, and contribute to the academic life and reputation of the University. This person will play an important role in the development of the “Computational Linguistics” branch of our curriculum and in establishing cross-disciplinary collaborations within and outside of the University.<br />
<br />
Requirements<br />
<br />
* Ph.D. in linguistics, computer science, or a related field.<br />
* Education in both linguistics and computer science, with a strong background in core linguistics.<br />
* Demonstrated interest in using computational techniques in the study of language.<br />
* Ability to teach in at least one of the core domains of linguistics.<br />
* Excellent publication track record in computational linguistics.<br />
* University teaching experience.<br />
* Sufficient knowledge of written and spoken French.<br />
<br />
Deadline: until December 13, 2018 inclusively<br />
<br />
Treatment: Université de Montréal offers competitive salaries and a full range of benefits.<br />
<br />
Starting date: On or after August 1st, 2019<br />
<br />
Application<br />
<br />
The application must include the following documents:<br />
* a cover letter<br />
* a curriculum vitæ<br />
* copies of recent publications and research<br />
<br />
Three letters of recommendation are also to be sent directly to the department chair by the referees.<br />
<br />
Application and letters of recommendation must be sent to the chair of the Département de linguistique et de traduction at the following address:<br />
<br />
Mireille Tremblay, directrice <br><br />
Département de linguistique et de traduction<br><br />
Faculté des arts et des sciences<br><br />
Université de Montréal<br><br />
C.P. 6128, succursale Centre-ville<br><br />
Montréal (QC) H3C 3J7<br><br />
Canada<br />
<br />
Application and letters of recommendation may also be sent by email at the following address: mireille.tremblay.4@umontreal.ca <br />
<br />
For more information about the Department, please consult its website at http://ling-trad.umontreal.ca<br />
<br />
Université de Montréal is a Québec university with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the world’s best specialists. In accordance with the institution’s language policy, Université de Montréal provides support for newly-recruited faculty to attain proficiency in French.<br />
<br />
The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview.<br />
<br />
Through its Equal Access Employment Program, Université de Montréal invites women, Aboriginal people, visible and ethnical minorities, as well as persons with disabilities to apply. During the recruitment process, our selection tools will be adapted to meet the needs of people with disabilities who request it. Be assured of the confidentiality of this information.<br />
<br />
Université de Montréal is committed to the inclusion and the diversity of its staff and also encourages people of all sexual and gender identities to apply.<br />
<br />
We invite all qualified candidates to apply at UdeM. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents.<br />
<br />
<br />
<br />
== Software Engineer for Text Mining Applications at the University of Manchester == <br />
<br />
* Employer: National Centre for Text Mining, School of Computer Science, University of Manchester<br />
* Title: Software Engineer<br />
* Specialty: Text Mining<br />
* Location: Manchester, UK<br />
* Deadline: November 25, 2018 <br />
* Date posted: October 25, 2018 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
Applications are invited for a Software Engineer post (full time) for a period of 5 years<br />
<br />
The successful candidate will be part of the National Centre for Text Mining (http://www.nactem.ac.uk/) which is hosted by the School of Computer Science, joining a strong and dynamic team in text mining. The National Centre for Text Mining provides next-generation text mining services to the community. We use natural language processing techniques to build advanced search systems in a number of domains. We are seeking a self-motivated, creative and experienced software engineer (must have substantive post graduation experience) to enhance our team expertise particularly in the areas of wrapping text mining analysis workflows, software development for search engines bringing the benefits of text mining to end users, Web services, integrating text mining with knowledge bases, cloud deployment of services and advanced user interfaces.<br />
<br />
Essential skills and experience include: Linux/unix, extensive experience of software design and development gained in a professional software development environment, experience of producing distributed solutions and of working with large datasets, Java or C++ with XML technologies, REST/SOAP Web services, knowledge of cloud/cluster computing/SaaS/PaaS, Maven.<br />
<br />
* Salary : £40,792 to £50,132 per annum dependent upon experience<br />
* Hours Per week: Full Time<br />
* Contract Duration : Starting 1 January 2019 for 5 years <br />
<br />
Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16308<br />
<br />
<br />
== Assistant Professor, Department of Linguistics, University of Florida == <br />
<br />
* Employer: Department of Linguistics, University of Florida<br />
* Title: Tenure-track Assistant Professor<br />
* Specialty: computational language science<br />
* Location: Gainesville, FL 32601<br />
* Deadline: November 18, 2018 <br />
* Date posted: October 18, 2018 <br />
* Contact: Stefanie Wulff <swulff@ufl.edu> and https://apply.interfolio.com/56557<br />
<br />
The University of Florida invites applications for a tenure-track appointment in computational language science at the rank of assistant professor, effective August 16, 2019. This is a 9-month position. Applicants are expected to have a Ph.D. in linguistics, computer science, or a closely-related field. Candidates should have an active research agenda studying language from a computational perspective. Specialization is open, including but not limited to sociolinguistics, neuro/psycholinguistics, corpus linguistics, and/or language documentation. UF Linguistics seeks to train the next generation of linguists who are comfortable integrating and evaluating computational approaches in their research. To this end, ability to teach computationally-oriented courses is required. Candidates must hold the Ph.D. by the starting date.<br />
<br />
The successful candidate will be expected to 1) maintain an active research agenda, 2) pursue external research funding, 3) teach two courses per semester at the undergraduate and/or graduate level, 4) provide service to the department, the university, and the profession, and 5) seek collaborations within the department as well as with other units on campus such as the UF Data Science and Information Technology Center, the UF Informatics Institute, or the McKnight Brain Institute.<br />
<br />
The Department is committed to creating an environment that affirms diversity and inclusion across a variety of dimensions, including ability, class, ethnicity/race, religion and/or cultural background, gender identity and expression. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service. The university and greater Gainesville community enjoy a diversity of cultural events, restaurants, year-round outdoor recreational activities, and social opportunities<br />
<br />
Salary is competitive, commensurate with qualifications and experience, and includes a full benefits package.<br />
<br />
The Linguistics Department at the University of Florida is a vibrant and congenial unit consisting of 11 full-time faculty and 15 affiliated faculty in the departments of Anthropology; Languages, Literatures, and Cultures; Spanish and Portuguese; and the Dial Center for Written & Oral Communication. We offer a B.A., M.A. and Ph.D. in Linguistics, as well as an undergraduate minor and undergraduate certificate in TESL and a graduate certificate in Second Language Acquisition and Teaching. We have faculty expertise in a wide range of linguistic subfields, and particular strengths in the areas of bilingualism, language documentation, psycholinguistics, sociolinguistics, and African linguistics. Please see our website, lin.ufl.edu, for more information about the department.<br />
<br />
For full consideration, applications must be submitted online at https://apply.interfolio.com/56557 and must include: (1) a brief cover letter, (2) a statement of teaching and research interests, (3) a CV, (4) 1-3 sample publications, (5) the names and email addresses for three references, and (6) representative teaching evaluations if available. After initial review, letters of recommendation will be requested for selected applicants. Review of applications will begin on 18 November 2018 and will continue until the position is filled.<br />
<br />
All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.<br />
<br />
The final candidate will be required to provide an official transcript to the department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.<br />
<br />
The University of Florida is an Equal Opportunity Employer dedicated to building a broadly diverse and inclusive faculty and staff. The University of Florida invites all qualified applicants, including minorities, women, veterans, and individuals with disabilities to apply. The University of Florida is a public institution and subject to all requirements under Florida Sunshine and Public Record laws.<br />
<br />
== Postdoctoral Researcher, Cognitive AI Lab, University of Arizona ==<br />
<br />
* Employer: School of Information, University of Arizona<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: natural language processing<br />
* Location: Tucson, AZ, USA<br />
* Deadline: Open until filled<br />
* Date posted: October 15, 2018<br />
* Contact: Peter Jansen <pajansen@email.arizona.edu><br />
<br />
Postdoctoral Research Associate I <br /><br />
https://uacareers.com/postings/31213 <br />
<br />
Position Summary <br /><br />
The Cognitive Artificial Intelligence Laboratory ( http://www.cognitiveai.org ) in the School of Information at the University of Arizona invites applications for a Postdoctoral Research Associate for projects specializing in natural language processing and explanation-centered inference.<br />
<br />
Natural language processing systems are steadily increasing performance on inference tasks like question answering, but few systems are able to provide explanations describing why their answers are correct. These explanations are critical in domains like science or medicine, where user trust is paramount and the cost of making errors is high. Our work has shown that one of the main barriers to increasing inference and explanation capability is the ability to combine information – for example, elementary science questions generally require combining between 6 and 12 different facts to answer and explain, but state-of-the-art systems generally struggle integrating more than two facts together. The successful candidate will combine novel methods in data collection, annotation, representation, and algorithmic development to exceed this limitation in combining information, and apply these methods to answering and explaining science questions. <br />
<br />
A talk on our recent work in this area is available here: https://www.youtube.com/watch?v=EneqL2sr6cQ<br />
<br />
Minimum Qualifications<br />
* A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.<br />
* Demonstrated interest in natural language processing or machine learning techniques.<br />
* Excellent verbal and written communication skills<br />
<br />
Duties and Responsibilities<br />
* Engage in innovative natural language processing research<br />
* Write and publish scientific articles describing methods and findings in high-quality venues (e.g. ACL, EMNLP, NAACL, etc.)<br />
* Assist in mentoring graduate and undergraduate students, and the management of ongoing projects<br />
* Support writing grant proposals for external funding opportunities<br />
* Serve as a collaborative member of a team of interdisciplinary researchers<br />
<br />
Preferred Qualifications<br />
* Knowledge of computational approaches to semantic knowledge representation, graph-based inference, and/or rule-based systems<br />
* Strong scholarly writing skills and publication record<br />
<br />
Full Posting/To Apply <br /><br />
https://uacareers.com/postings/31213<br />
<br />
== Temporary lecturer, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Lecturer<br />
* Specialty: computational linguistics and/or natural language processing and general linguistics<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: October 24, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01317<br />
<br />
The Department of Linguistics at the University of California, Santa Barbara invites applications for a qualified temporary Lecturer to teach course(s) in computational linguistics and potentially general linguistics. To learn more about the department, see: http://www.linguistics.ucsb.edu/<br />
<br />
The Lecturer will teach an advanced undergraduate course in computational linguistics in the Winter 2019 or Spring 2019 quarter. The successful candidate may also have the opportunity to teach other courses that support the department’s undergraduate programs, including classes currently listed in the UCSB general catalog and/or special-topic courses proposed by the applicant; these courses may be offered in Winter 2019 or Spring 2019.<br />
<br />
Applicants must possess a Master’s Degree in Linguistics and have at least one year teaching college-level linguistics courses. A Ph.D. in Linguistics is preferred but not required. The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
To apply, please go to the following link: https://recruit.ap.ucsb.edu/apply/JPF01317. Applicants should submit a curriculum vitae and a cover letter stating their qualifications for teaching computational linguistics as well as any additional courses they may be interested in teaching. Applicants should also provide contact information for three references. To ensure full consideration, all application materials should be received by 10/24/18; however, the position is open until filled. <br />
<br />
The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Assistant Professor, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Assistant Professor<br />
* Specialty: computational linguistics and/or natural language processing<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: November 9, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01310 and complingsearch@linguistics.ucsb.edu<br />
<br />
The Linguistics Department of the University of California, Santa Barbara seeks to hire a linguist who is a specialist in computational linguistics and/or natural language processing. The appointment will be a tenure-track position at the Assistant Professor level, effective July 1, 2019.<br />
<br />
The successful candidate will have an active research program in computational linguistics and/or natural language processing and will have a record of participation in the computational linguistics/NLP community. Proven expertise in machine learning including word embeddings/vector space semantics is required, as is expertise in using computational linguistics methods to address theoretical and/or applied questions. Capacity to engage with the distinctive theoretical orientation of the department is expected. We welcome applicants with the ability to contribute to departmental foci, such as corpus linguistics, language and cognition, language acquisition, and/or less studied languages. We also encourage applicants who have the potential to interact with colleagues and students across disciplinary boundaries at UCSB.<br />
<br />
The successful candidate will demonstrate commitment to and ability in graduate and undergraduate teaching and will be expected to teach a range of graduate and undergraduate courses in computational linguistics, including those with relevance to industry, as well as to contribute to the department’s undergraduate major with an emphasis in Language and Speech Technologies. For more information on the department, see www.linguistics.ucsb.edu.<br />
<br />
The minimum requirement to be considered as an applicant is the completion of all requirements for a Ph.D. in linguistics or a closely-related field except the dissertation (or equivalent) at the time of application. A Ph.D. in linguistics or a closely-related field is expected by the time of appointment. Review of applications will begin after Friday, November 9, 2018. The position will remain open until filled. <br />
<br />
Applicants must complete the online form at https://recruit.ap.ucsb.edu/apply/JPF01310 and must submit online the following in PDF format: letter of application, statement of research interests, teaching statement, curriculum vitae, and 2 writing samples. Applicants are also encouraged to submit an optional statement on contributions to diversity. <br />
<br />
Applicants should request 3-5 letters of reference to be sent directly to https://recruit.ap.ucsb.edu/reference. Inquiries may be addressed to the Search Committee at complingsearch@linguistics.ucsb.edu. Initial screening of selected applicants will be conducted via Zoom. Our department has a genuine commitment to diversity, and is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
The University of California is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Postdoctoral Fellow, Quantitative Criticism Lab, University of Texas at Austin ==<br />
<br />
* Employer: Quantitative Criticism Lab, University of Texas at Austin<br />
* Title: Postdoctoral Fellow<br />
* Specialty: Digital humanities and natural language processing<br />
* Location: Austin, TX or remote<br />
* Deadline: October 15, 2018<br />
* Date posted: September 7, 2018<br />
* Contact: https://www.nature.com/naturejobs/science/jobs/652327-postdoctoral-fellow<br />
<br />
The Quantitative Criticism Lab (QCL; https://www.qcrit.org), a research group developing cross-disciplinary approaches to the study of literature and culture, invites applications for a full-time postdoctoral fellowship. The duration of the fellowship is 18 months, from January 2, 2019 to June 30, 2020. The field of specialization is open, but expertise in computer programming and statistical analysis is essential, as is a deep interest in the study of literature. QCL’s physical lab space is based at The University of Texas at Austin; residence in Austin during the fellowship period is preferred but not required. The fellow will have no teaching responsibilities. The position is funded by a Digital Extension Grant from the American Council of Learned Societies (ACLS).<br />
<br />
The ACLS-funded project will produce a web-based suite of tools for traditionally-trained humanists to analyze literary texts in a quantitative manner. The tools are designed with an important class of literary problems in mind, exemplified by the identification of verbal parallels and, at a larger scale, by the individuating of entire works within generic traditions. We take two main approaches: sequence alignment for the detection of verbal resemblance, and stylometry augmented by machine learning for the profiling of texts and corpora. The tools are expected both to enhance traditional modes of literary criticism and to enable novel quantitative analyses of the cultural evolution of literature.<br />
<br />
The postdoctoral fellow’s primary responsibilities will be to lead development of these tools and to participate in other aspects of QCL’s research program according to background and interests. The work will involve coding, research design, data analysis, literary criticism, and scholarly writing for diverse venues, as well as various organizational duties related to workshops and conferences. The postdoctoral fellow will work under the supervision of Pramit Chaudhuri (UT Austin) and Joseph Dexter (Dartmouth College), the co-directors of QCL, and will collaborate with a diverse array of scholars, in both academia and industry, affiliated with QCL. In addition, the fellow will be expected to play a major role in mentoring the numerous graduate, undergraduate, and high school students who conduct research with QCL.<br />
<br />
A Ph.D. in a computational, statistical, linguistic, or literary field is required. Possible disciplines include (but are not limited to) anthropology, applied mathematics, bioinformatics, classics, comparative literature, computer science, English, evolutionary biology, linguistics, and statistics. Prior experience with any of the following areas is highly desirable but not required: computational linguistics, cultural evolution, digital humanities, literary criticism of a premodern or non-Anglophone tradition (especially Latin or Ancient Greek), machine learning, and natural language processing. By the start date of the position, applicants should either have the Ph.D. in hand or be able to provide certification from their home institution that all degree requirements have been fulfilled. Applicants must have received the Ph.D. within the last three years.<br />
<br />
For full consideration, applicants should submit the following materials by October 15, 2018:<br />
<br />
# CV;<br />
# Cover letter;<br />
# Short (2-4 page) summary of past and current research interests, giving particular attention to any computational work;<br />
# Writing sample of no more than 40 pages (e.g., article or dissertation chapter).<br />
<br />
In addition, applicants should arrange to have three letters of recommendation forwarded by the deadline. Please submit your CV and cover letter on the UT Jobs website: https://utdirect.utexas.edu/apps/hr/jobs/nlogon/180823010712. Please submit the additional materials via email to vnoya@austin.utexas.edu. Questions can be directed to Vanessa Noya at the same address.<br />
<br />
The salary will be $48,000 per year, plus benefits.<br />
<br />
The successful candidate must be able to begin work in this position by January 2, 2019.<br />
<br />
A criminal history background check will be required for finalist(s) under consideration for this position.<br />
<br />
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.<br />
<br />
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.<br />
<br />
If hired, you will be required to complete the federal Employment Eligibility Verification form, I-9. You will be required to present acceptable, original documents (https://hr.utexas.edu/current/services/employment-eligibility-verification-i9-docs) to prove your identity and authorization to work in the United States. Information from the documents will be submitted to the federal E-Verify system for verification. Documents must be presented no later than the third day of employment. Failure to do so will result in dismissal.<br />
<br />
UT Austin is a Tobacco-free Campus (http://tobaccofree.utexas.edu/). <br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: September 30, 2018 (or until filled)<br />
* Date posted: September 6, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities. <br />
<br />
Possible areas of research include, but are not limited to:<br />
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;<br />
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;<br />
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;<br />
* joint text and image processing for content classification in social media, e.g. identifying bias;<br />
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.<br />
<br />
The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.<br />
<br />
We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab. <br />
<br />
The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining. UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Tenure-track and tenure-eligible investigators at the National Library of Medicine, Bethesda, Maryland ==<br />
*Employer: National Library of Medicine<br />
*Title: Tenure-track and tenure-eligible investigators <br />
*Specialty: Natural Language Processing <br />
*Location: Bethesda, MD, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: August 15, 2018<br />
*Contact: Dr. Andy Baxevanis, the Search Chair, <andy@mail.nih.gov><br />
<br />
The National Library of Medicine is currently recruiting for both tenure-track and tenure-eligible investigators in data science, biomedical informatics, and computational biology. <br />
Individuals with significant experience in the use of statistical, machine learning, optimization and advanced mathematical methodologies as applied to biomedical and health science are encouraged to apply. <br />
Additional details are available by following the links below. <br />
<br />
https://www.nlm.nih.gov/careers/jobopenings.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_01_20180813.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_02_20180813.html<br />
<br />
<br />
<br />
== Question-Answering Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: Question-answering <br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: July 3, 2018<br />
*Contact: Franck Dernoncourt <dernonco@adobe.com><br />
<br />
We are looking for a PhD student with background in question-answering for a late summer or autumn, ~13-week internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile).<br />
<br />
== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Natural language understanding, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The principal investigator is Prof. Sien Moens. CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world.<br />
<br />
The successful candidate will have an opportunity to work on innovative natural language understanding research such as grounding language meaning into visual perception and translating narrative language into visual events. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.<br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Perform own research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.<br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organisation of student seminars, and the supervision of bachelor and master theses. <br />
* Help in the supervision of PhD researchers of the CALCULUS team.<br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in fundamental research in language understanding and machine learning. <br />
* You are not afraid of creative and original ideas and solutions.<br />
* You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.<br />
* You are good at collaborating with and leading others.<br />
* You work proactively and independently and have good communication skills.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
* We offer a 2 x 2-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences and for short research stays.<br />
<br />
'''Interested'''<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Text mining, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data. The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners. <br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Design and develop machine learning methods for multilingual text mining. <br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses. <br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. <br />
* You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.<br />
* You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
<br />
* We offer a two-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences.<br />
<br />
'''Interested'''<br />
<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==<br />
<br />
* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: deep learning, summarization<br />
* Location: Darmstadt<br />
* Deadline: June 27, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [http://www.aiphes.tu-darmstadt.de/ Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling two positions for three years, <br />
starting as soon as possible, located in Darmstadt and associated with <br />
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
The positions provide the opportunity to obtain a doctoral degree with <br />
an emphasis in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, abstractive summarization, or a related area. <br />
Applicants should be willing to work on cross-lingual, cross-modality <br />
and domain-independent methods. Prior experience in transfer learning, <br />
multi-task learning, adversarial learning, deep reinforcement learning <br />
or related methods is a plus.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, computer vision, and data and information management <br />
will be developed. AIPHES investigates a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
benefit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. <br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning <br />
(Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). AIPHES strives to publish its results at <br />
leading <br />
scientific conferences and is actively supporting its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Machine Learning, NLP, or a related study <br />
program. We expect the ability to work independently, personal <br />
commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Prior experience in <br />
scientific work is a plus. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [https://www.ukp.tu-darmstadt.de UKP Lab] is a highly dynamic research group committed to <br />
top-level conferences, technologies of the highest standards, <br />
cooperative work style and close interaction of team members. Its <br />
BMBF-funded Centre for the Digital Foundation of Research in the <br />
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, <br />
machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a <br />
user-defined topic: neural networks determine relevant pro and con <br />
arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of <br />
the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in electronic form. Application materials must be submitted via the <br />
following form by June, 27th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
== Postdoc position: Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University<br />
*Title: Postdoctoral Researcher<br />
*Location: Milan, Italy<br />
*Deadline: June 22nd, 2018, 5 p.m. <br />
*Starting date: as early as possible, but no later than September 2018<br />
*Duration: 1 year <br />
*Date Posted: June 18, 2018<br />
*Contact: Paola Cillo (paola.cillo@unibocconi.it) <br />
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)<br />
<br />
Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.<br />
<br />
REQUIREMENTS/QUALIFICATIONS <br />
<br />
The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks. The candidate is expected to have:<br />
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.<br />
* Good programming skills in Python.<br />
* Fluent English. Knowledge of other languages is more than welcome. Knowledge of Italian is NOT a requirement.<br />
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).<br />
* Publications in top-tier venues in the field of Computational Linguistics.<br />
* Experience in Ph.D. student supervision is a plus.<br />
* Salary: 43,310.50 euros per annum<br />
<br />
HOW TO APPLY <br />
<br />
The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it <br />
You can find more information about the project and call here: https://bit.ly/2t1DnAO<br />
<br />
== Postdocs: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Postdoctoral Researcher<br />
*Location: Baltimore, MD<br />
*Deadline: Applications will be accepted until positions are filled<br />
*Date Posted: June 6, 2018<br />
*Contact: clspsearch@clsp.jhu.edu<br />
*URL: https://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.<br />
<br />
Example topics include:<br />
* Cross-lingual Information Retrieval<br />
* Trend Detection in Social Media<br />
* Social Media and Mental Health<br />
* Analysis of Clinical Medical Text<br />
* Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation<br />
* NLP and Machine Learning for Clinical Data Analysis<br />
<br />
Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.<br />
<br />
CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.<br />
<br />
Applicants are not required to be to US citizens or permanent residents.<br />
<br />
Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.<br />
<br />
Details and application information:<br />
http://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
<br />
== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==<br />
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]<br />
* Title: Research Fellow <br />
* Speciality: Software engineering, machine learning, natural language processing<br />
* Location: Tartu, Estonia<br />
* Deadline: June 4, 2018<br />
* Date posted: May 21, 2018<br />
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)<br />
<br />
'''Postdoctoral position''' <br/><br />
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.<br />
<br />
The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:<br />
<br />
* open innovation,<br />
* energy-efficient software development,<br />
* software testing.<br />
<br />
The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.<br />
<br />
'''Requirements''' <br/><br />
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.<br />
<br />
The expected start date is 1 September 2018, but a later start date can be negotiated.<br />
<br />
The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].<br />
<br />
== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==<br />
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design<br />
* Location: Albany, New York, USA <br />
* Deadline: July 31, 2018<br />
* Date posted: May 18, 2018<br />
* Contact: Tomek Strzalkowski (tomek {at} albany.edu) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* ''The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project.'' The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.<br />
* ''The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project.'' The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information. <br />
<br />
'''Requirements for the PANACEA position''' <br/><br />
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.<br />
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus. <br />
<br />
'''Requirements for the COMETH positions''' <br/><br />
For the COMETH project, we seek '''two''' postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.<br />
<br />
* The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus. <br />
* The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.<br />
<br />
'''Overall Requirements''' <br/><br />
* For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.<br />
<br />
The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.<br />
<br />
'''How to Apply''' <br/> <br />
<br />
Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu <br />
<br />
== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Two PhD positions <br />
* Speciality: Natural Language Understanding, Summarisation, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: May 31, 2018<br />
* Date posted: April 30, 2018<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Two PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.<br />
<br />
The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.<br />
<br />
This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.<br />
<br />
The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills. <br />
<br />
The successful PhD candidates will join the [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group] at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at [http://www.epfl.ch EPFL] conditional on parallel application to, and acceptance by, the [http://phd.epfl.ch/applicants EPFL Doctoral School]. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online here:<br />
[http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D]<br />
<br />
'''Idiap'''<br />
<br />
Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.<br />
<br />
<br />
<br />
== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Text mining, natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.<br />
* Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*PhD in computer science or equivalent.<br />
* Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.<br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: PhD researcher <br />
* Speciality: Natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''PhD positions''' <br/><br />
<br />
* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*Master degree in computer science or equivalent.<br />
*Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization. <br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12335Employment opportunities, postdoctoral positions, summer jobs2018-11-22T12:37:39Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt (PhD-level)</p>
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<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Text Analysis and Natural Language Processing Tools<br />
* Location: Darmstadt<br />
* Deadline: December 15, 2018 (or until filled)<br />
* Date posted: November 22, 2018<br />
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of ''Interactive Text Analysis'' and ''Natural Language Processing Tools''. The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of ''Natural Language Processing'' (NLP), with a rapidly developing focus on Interactive Machine Learning. Besides, we provide a range of high-quality open source software packages for interactive and automatic text analysis to research and industry communities and collaborate with both academic and industrial partners.<br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Semantic Web Technologies and either Information Retrieval or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German.<br />
<br />
The successful applicant will work on research and development for interactive text annotation by end-users (researchers, analysts, etc.). This includes neural network-based methods for knowledge graph construction and completion, interactive sequence labeling recommender systems, or semantic information retrieval. We integrate the results in a real-life collaborative text annotation software for large-scale interactive corpus analysis.<br />
<br />
Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems (frontend and backend), in applying NLP-related Machine Learning-based methods (e.g. learning-to-rank, clustering, etc.), experience with information retrieval systems (e.g. Lucene, Solr, ElasticSearch) and relational databases (SQL), semantic web technologies (e.g. RDF, OWL, SPARQL), and strong programming skills especially in Java. Experience with neural network architectures (e.g. knowledge-base embeddings) and demonstrable engagement in open- source projects are a strong plus.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: December 15, 2018 (or until filled)<br />
* Date posted: November 22, 2018<br />
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD- or (Senior-)PostDoc level; for an initial term of two years)'''<br />
<br />
The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of ''Natural Language Processing'' (NLP), with an emphasis on semantic text analysis and generation, argument mining, and interactive machine learning. Besides, we have a strong profile in deep learning for NLP, construction of large-scale benchmarks, or knowledge graphs. We collaborate with a wide range of both academic and industrial partners.<br />
<br />
We are looking for candidates in Computer Science with a specialization in Natural Language Processing, preferably with expertise in research and development projects, prior publication experience, and strong communication skills. The research topics of the position may include: NLP in low-research settings, argument mining and retrieval, multimodal content processing, privacy-enhanced NLP as well as machine learning for NLP (deep reinforcement learning, neural network architectures). The successful applicant will work on research and development as part of a team in one of the areas above. We disseminate the results in top venues of the field and as free research software and datasets. The lab offers highly attractive options for personal growth and career development at all levels of the scientific career. Upon interest, additional qualifications in teaching and project management can be acquired.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Assistant Professor, Department of Linguistics and Translation, University of Montreal == <br />
<br />
* Employer: Department of Linguistics and Translation, University of Montreal<br />
* Title: Assistant Professor (tenure-track)<br />
* Specialty: Computational linguistics<br />
* Location: Montreal, Canada<br />
* Deadline: December 13, 2018 <br />
* Date posted: November 10, 2018 <br />
* Contact: Mireille Tremblay <mireille.tremblay.4@umontreal.ca > and https://ling-trad.umontreal.ca<br />
<br />
The Département de linguistique et de traduction is seeking applications for a full-time tenure-track position at the rank of Assistant Professor in computational linguistics/natural language processing.<br />
<br />
Responsibilities<br />
<br />
The appointed candidate will be expected to teach at all three levels of the curriculum, supervise graduate students, engage in ongoing research and publication, and contribute to the academic life and reputation of the University. This person will play an important role in the development of the “Computational Linguistics” branch of our curriculum and in establishing cross-disciplinary collaborations within and outside of the University.<br />
<br />
Requirements<br />
<br />
* Ph.D. in linguistics, computer science, or a related field.<br />
* Education in both linguistics and computer science, with a strong background in core linguistics.<br />
* Demonstrated interest in using computational techniques in the study of language.<br />
* Ability to teach in at least one of the core domains of linguistics.<br />
* Excellent publication track record in computational linguistics.<br />
* University teaching experience.<br />
* Sufficient knowledge of written and spoken French.<br />
<br />
Deadline: until December 13, 2018 inclusively<br />
<br />
Treatment: Université de Montréal offers competitive salaries and a full range of benefits.<br />
<br />
Starting date: On or after August 1st, 2019<br />
<br />
Application<br />
<br />
The application must include the following documents:<br />
* a cover letter<br />
* a curriculum vitæ<br />
* copies of recent publications and research<br />
<br />
Three letters of recommendation are also to be sent directly to the department chair by the referees.<br />
<br />
Application and letters of recommendation must be sent to the chair of the Département de linguistique et de traduction at the following address:<br />
<br />
Mireille Tremblay, directrice <br><br />
Département de linguistique et de traduction<br><br />
Faculté des arts et des sciences<br><br />
Université de Montréal<br><br />
C.P. 6128, succursale Centre-ville<br><br />
Montréal (QC) H3C 3J7<br><br />
Canada<br />
<br />
Application and letters of recommendation may also be sent by email at the following address: mireille.tremblay.4@umontreal.ca <br />
<br />
For more information about the Department, please consult its website at http://ling-trad.umontreal.ca<br />
<br />
Université de Montréal is a Québec university with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the world’s best specialists. In accordance with the institution’s language policy, Université de Montréal provides support for newly-recruited faculty to attain proficiency in French.<br />
<br />
The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview.<br />
<br />
Through its Equal Access Employment Program, Université de Montréal invites women, Aboriginal people, visible and ethnical minorities, as well as persons with disabilities to apply. During the recruitment process, our selection tools will be adapted to meet the needs of people with disabilities who request it. Be assured of the confidentiality of this information.<br />
<br />
Université de Montréal is committed to the inclusion and the diversity of its staff and also encourages people of all sexual and gender identities to apply.<br />
<br />
We invite all qualified candidates to apply at UdeM. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents.<br />
<br />
<br />
<br />
== Software Engineer for Text Mining Applications at the University of Manchester == <br />
<br />
* Employer: National Centre for Text Mining, School of Computer Science, University of Manchester<br />
* Title: Software Engineer<br />
* Specialty: Text Mining<br />
* Location: Manchester, UK<br />
* Deadline: November 25, 2018 <br />
* Date posted: October 25, 2018 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
Applications are invited for a Software Engineer post (full time) for a period of 5 years<br />
<br />
The successful candidate will be part of the National Centre for Text Mining (http://www.nactem.ac.uk/) which is hosted by the School of Computer Science, joining a strong and dynamic team in text mining. The National Centre for Text Mining provides next-generation text mining services to the community. We use natural language processing techniques to build advanced search systems in a number of domains. We are seeking a self-motivated, creative and experienced software engineer (must have substantive post graduation experience) to enhance our team expertise particularly in the areas of wrapping text mining analysis workflows, software development for search engines bringing the benefits of text mining to end users, Web services, integrating text mining with knowledge bases, cloud deployment of services and advanced user interfaces.<br />
<br />
Essential skills and experience include: Linux/unix, extensive experience of software design and development gained in a professional software development environment, experience of producing distributed solutions and of working with large datasets, Java or C++ with XML technologies, REST/SOAP Web services, knowledge of cloud/cluster computing/SaaS/PaaS, Maven.<br />
<br />
* Salary : £40,792 to £50,132 per annum dependent upon experience<br />
* Hours Per week: Full Time<br />
* Contract Duration : Starting 1 January 2019 for 5 years <br />
<br />
Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16308<br />
<br />
<br />
== Assistant Professor, Department of Linguistics, University of Florida == <br />
<br />
* Employer: Department of Linguistics, University of Florida<br />
* Title: Tenure-track Assistant Professor<br />
* Specialty: computational language science<br />
* Location: Gainesville, FL 32601<br />
* Deadline: November 18, 2018 <br />
* Date posted: October 18, 2018 <br />
* Contact: Stefanie Wulff <swulff@ufl.edu> and https://apply.interfolio.com/56557<br />
<br />
The University of Florida invites applications for a tenure-track appointment in computational language science at the rank of assistant professor, effective August 16, 2019. This is a 9-month position. Applicants are expected to have a Ph.D. in linguistics, computer science, or a closely-related field. Candidates should have an active research agenda studying language from a computational perspective. Specialization is open, including but not limited to sociolinguistics, neuro/psycholinguistics, corpus linguistics, and/or language documentation. UF Linguistics seeks to train the next generation of linguists who are comfortable integrating and evaluating computational approaches in their research. To this end, ability to teach computationally-oriented courses is required. Candidates must hold the Ph.D. by the starting date.<br />
<br />
The successful candidate will be expected to 1) maintain an active research agenda, 2) pursue external research funding, 3) teach two courses per semester at the undergraduate and/or graduate level, 4) provide service to the department, the university, and the profession, and 5) seek collaborations within the department as well as with other units on campus such as the UF Data Science and Information Technology Center, the UF Informatics Institute, or the McKnight Brain Institute.<br />
<br />
The Department is committed to creating an environment that affirms diversity and inclusion across a variety of dimensions, including ability, class, ethnicity/race, religion and/or cultural background, gender identity and expression. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service. The university and greater Gainesville community enjoy a diversity of cultural events, restaurants, year-round outdoor recreational activities, and social opportunities<br />
<br />
Salary is competitive, commensurate with qualifications and experience, and includes a full benefits package.<br />
<br />
The Linguistics Department at the University of Florida is a vibrant and congenial unit consisting of 11 full-time faculty and 15 affiliated faculty in the departments of Anthropology; Languages, Literatures, and Cultures; Spanish and Portuguese; and the Dial Center for Written & Oral Communication. We offer a B.A., M.A. and Ph.D. in Linguistics, as well as an undergraduate minor and undergraduate certificate in TESL and a graduate certificate in Second Language Acquisition and Teaching. We have faculty expertise in a wide range of linguistic subfields, and particular strengths in the areas of bilingualism, language documentation, psycholinguistics, sociolinguistics, and African linguistics. Please see our website, lin.ufl.edu, for more information about the department.<br />
<br />
For full consideration, applications must be submitted online at https://apply.interfolio.com/56557 and must include: (1) a brief cover letter, (2) a statement of teaching and research interests, (3) a CV, (4) 1-3 sample publications, (5) the names and email addresses for three references, and (6) representative teaching evaluations if available. After initial review, letters of recommendation will be requested for selected applicants. Review of applications will begin on 18 November 2018 and will continue until the position is filled.<br />
<br />
All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.<br />
<br />
The final candidate will be required to provide an official transcript to the department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.<br />
<br />
The University of Florida is an Equal Opportunity Employer dedicated to building a broadly diverse and inclusive faculty and staff. The University of Florida invites all qualified applicants, including minorities, women, veterans, and individuals with disabilities to apply. The University of Florida is a public institution and subject to all requirements under Florida Sunshine and Public Record laws.<br />
<br />
== Postdoctoral Researcher, Cognitive AI Lab, University of Arizona ==<br />
<br />
* Employer: School of Information, University of Arizona<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: natural language processing<br />
* Location: Tucson, AZ, USA<br />
* Deadline: Open until filled<br />
* Date posted: October 15, 2018<br />
* Contact: Peter Jansen <pajansen@email.arizona.edu><br />
<br />
Postdoctoral Research Associate I <br /><br />
https://uacareers.com/postings/31213 <br />
<br />
Position Summary <br /><br />
The Cognitive Artificial Intelligence Laboratory ( http://www.cognitiveai.org ) in the School of Information at the University of Arizona invites applications for a Postdoctoral Research Associate for projects specializing in natural language processing and explanation-centered inference.<br />
<br />
Natural language processing systems are steadily increasing performance on inference tasks like question answering, but few systems are able to provide explanations describing why their answers are correct. These explanations are critical in domains like science or medicine, where user trust is paramount and the cost of making errors is high. Our work has shown that one of the main barriers to increasing inference and explanation capability is the ability to combine information – for example, elementary science questions generally require combining between 6 and 12 different facts to answer and explain, but state-of-the-art systems generally struggle integrating more than two facts together. The successful candidate will combine novel methods in data collection, annotation, representation, and algorithmic development to exceed this limitation in combining information, and apply these methods to answering and explaining science questions. <br />
<br />
A talk on our recent work in this area is available here: https://www.youtube.com/watch?v=EneqL2sr6cQ<br />
<br />
Minimum Qualifications<br />
* A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.<br />
* Demonstrated interest in natural language processing or machine learning techniques.<br />
* Excellent verbal and written communication skills<br />
<br />
Duties and Responsibilities<br />
* Engage in innovative natural language processing research<br />
* Write and publish scientific articles describing methods and findings in high-quality venues (e.g. ACL, EMNLP, NAACL, etc.)<br />
* Assist in mentoring graduate and undergraduate students, and the management of ongoing projects<br />
* Support writing grant proposals for external funding opportunities<br />
* Serve as a collaborative member of a team of interdisciplinary researchers<br />
<br />
Preferred Qualifications<br />
* Knowledge of computational approaches to semantic knowledge representation, graph-based inference, and/or rule-based systems<br />
* Strong scholarly writing skills and publication record<br />
<br />
Full Posting/To Apply <br /><br />
https://uacareers.com/postings/31213<br />
<br />
== Temporary lecturer, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Lecturer<br />
* Specialty: computational linguistics and/or natural language processing and general linguistics<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: October 24, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01317<br />
<br />
The Department of Linguistics at the University of California, Santa Barbara invites applications for a qualified temporary Lecturer to teach course(s) in computational linguistics and potentially general linguistics. To learn more about the department, see: http://www.linguistics.ucsb.edu/<br />
<br />
The Lecturer will teach an advanced undergraduate course in computational linguistics in the Winter 2019 or Spring 2019 quarter. The successful candidate may also have the opportunity to teach other courses that support the department’s undergraduate programs, including classes currently listed in the UCSB general catalog and/or special-topic courses proposed by the applicant; these courses may be offered in Winter 2019 or Spring 2019.<br />
<br />
Applicants must possess a Master’s Degree in Linguistics and have at least one year teaching college-level linguistics courses. A Ph.D. in Linguistics is preferred but not required. The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
To apply, please go to the following link: https://recruit.ap.ucsb.edu/apply/JPF01317. Applicants should submit a curriculum vitae and a cover letter stating their qualifications for teaching computational linguistics as well as any additional courses they may be interested in teaching. Applicants should also provide contact information for three references. To ensure full consideration, all application materials should be received by 10/24/18; however, the position is open until filled. <br />
<br />
The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Assistant Professor, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Assistant Professor<br />
* Specialty: computational linguistics and/or natural language processing<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: November 9, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01310 and complingsearch@linguistics.ucsb.edu<br />
<br />
The Linguistics Department of the University of California, Santa Barbara seeks to hire a linguist who is a specialist in computational linguistics and/or natural language processing. The appointment will be a tenure-track position at the Assistant Professor level, effective July 1, 2019.<br />
<br />
The successful candidate will have an active research program in computational linguistics and/or natural language processing and will have a record of participation in the computational linguistics/NLP community. Proven expertise in machine learning including word embeddings/vector space semantics is required, as is expertise in using computational linguistics methods to address theoretical and/or applied questions. Capacity to engage with the distinctive theoretical orientation of the department is expected. We welcome applicants with the ability to contribute to departmental foci, such as corpus linguistics, language and cognition, language acquisition, and/or less studied languages. We also encourage applicants who have the potential to interact with colleagues and students across disciplinary boundaries at UCSB.<br />
<br />
The successful candidate will demonstrate commitment to and ability in graduate and undergraduate teaching and will be expected to teach a range of graduate and undergraduate courses in computational linguistics, including those with relevance to industry, as well as to contribute to the department’s undergraduate major with an emphasis in Language and Speech Technologies. For more information on the department, see www.linguistics.ucsb.edu.<br />
<br />
The minimum requirement to be considered as an applicant is the completion of all requirements for a Ph.D. in linguistics or a closely-related field except the dissertation (or equivalent) at the time of application. A Ph.D. in linguistics or a closely-related field is expected by the time of appointment. Review of applications will begin after Friday, November 9, 2018. The position will remain open until filled. <br />
<br />
Applicants must complete the online form at https://recruit.ap.ucsb.edu/apply/JPF01310 and must submit online the following in PDF format: letter of application, statement of research interests, teaching statement, curriculum vitae, and 2 writing samples. Applicants are also encouraged to submit an optional statement on contributions to diversity. <br />
<br />
Applicants should request 3-5 letters of reference to be sent directly to https://recruit.ap.ucsb.edu/reference. Inquiries may be addressed to the Search Committee at complingsearch@linguistics.ucsb.edu. Initial screening of selected applicants will be conducted via Zoom. Our department has a genuine commitment to diversity, and is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
The University of California is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Postdoctoral Fellow, Quantitative Criticism Lab, University of Texas at Austin ==<br />
<br />
* Employer: Quantitative Criticism Lab, University of Texas at Austin<br />
* Title: Postdoctoral Fellow<br />
* Specialty: Digital humanities and natural language processing<br />
* Location: Austin, TX or remote<br />
* Deadline: October 15, 2018<br />
* Date posted: September 7, 2018<br />
* Contact: https://www.nature.com/naturejobs/science/jobs/652327-postdoctoral-fellow<br />
<br />
The Quantitative Criticism Lab (QCL; https://www.qcrit.org), a research group developing cross-disciplinary approaches to the study of literature and culture, invites applications for a full-time postdoctoral fellowship. The duration of the fellowship is 18 months, from January 2, 2019 to June 30, 2020. The field of specialization is open, but expertise in computer programming and statistical analysis is essential, as is a deep interest in the study of literature. QCL’s physical lab space is based at The University of Texas at Austin; residence in Austin during the fellowship period is preferred but not required. The fellow will have no teaching responsibilities. The position is funded by a Digital Extension Grant from the American Council of Learned Societies (ACLS).<br />
<br />
The ACLS-funded project will produce a web-based suite of tools for traditionally-trained humanists to analyze literary texts in a quantitative manner. The tools are designed with an important class of literary problems in mind, exemplified by the identification of verbal parallels and, at a larger scale, by the individuating of entire works within generic traditions. We take two main approaches: sequence alignment for the detection of verbal resemblance, and stylometry augmented by machine learning for the profiling of texts and corpora. The tools are expected both to enhance traditional modes of literary criticism and to enable novel quantitative analyses of the cultural evolution of literature.<br />
<br />
The postdoctoral fellow’s primary responsibilities will be to lead development of these tools and to participate in other aspects of QCL’s research program according to background and interests. The work will involve coding, research design, data analysis, literary criticism, and scholarly writing for diverse venues, as well as various organizational duties related to workshops and conferences. The postdoctoral fellow will work under the supervision of Pramit Chaudhuri (UT Austin) and Joseph Dexter (Dartmouth College), the co-directors of QCL, and will collaborate with a diverse array of scholars, in both academia and industry, affiliated with QCL. In addition, the fellow will be expected to play a major role in mentoring the numerous graduate, undergraduate, and high school students who conduct research with QCL.<br />
<br />
A Ph.D. in a computational, statistical, linguistic, or literary field is required. Possible disciplines include (but are not limited to) anthropology, applied mathematics, bioinformatics, classics, comparative literature, computer science, English, evolutionary biology, linguistics, and statistics. Prior experience with any of the following areas is highly desirable but not required: computational linguistics, cultural evolution, digital humanities, literary criticism of a premodern or non-Anglophone tradition (especially Latin or Ancient Greek), machine learning, and natural language processing. By the start date of the position, applicants should either have the Ph.D. in hand or be able to provide certification from their home institution that all degree requirements have been fulfilled. Applicants must have received the Ph.D. within the last three years.<br />
<br />
For full consideration, applicants should submit the following materials by October 15, 2018:<br />
<br />
# CV;<br />
# Cover letter;<br />
# Short (2-4 page) summary of past and current research interests, giving particular attention to any computational work;<br />
# Writing sample of no more than 40 pages (e.g., article or dissertation chapter).<br />
<br />
In addition, applicants should arrange to have three letters of recommendation forwarded by the deadline. Please submit your CV and cover letter on the UT Jobs website: https://utdirect.utexas.edu/apps/hr/jobs/nlogon/180823010712. Please submit the additional materials via email to vnoya@austin.utexas.edu. Questions can be directed to Vanessa Noya at the same address.<br />
<br />
The salary will be $48,000 per year, plus benefits.<br />
<br />
The successful candidate must be able to begin work in this position by January 2, 2019.<br />
<br />
A criminal history background check will be required for finalist(s) under consideration for this position.<br />
<br />
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.<br />
<br />
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.<br />
<br />
If hired, you will be required to complete the federal Employment Eligibility Verification form, I-9. You will be required to present acceptable, original documents (https://hr.utexas.edu/current/services/employment-eligibility-verification-i9-docs) to prove your identity and authorization to work in the United States. Information from the documents will be submitted to the federal E-Verify system for verification. Documents must be presented no later than the third day of employment. Failure to do so will result in dismissal.<br />
<br />
UT Austin is a Tobacco-free Campus (http://tobaccofree.utexas.edu/). <br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: September 30, 2018 (or until filled)<br />
* Date posted: September 6, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities. <br />
<br />
Possible areas of research include, but are not limited to:<br />
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;<br />
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;<br />
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;<br />
* joint text and image processing for content classification in social media, e.g. identifying bias;<br />
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.<br />
<br />
The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.<br />
<br />
We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab. <br />
<br />
The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining. UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Tenure-track and tenure-eligible investigators at the National Library of Medicine, Bethesda, Maryland ==<br />
*Employer: National Library of Medicine<br />
*Title: Tenure-track and tenure-eligible investigators <br />
*Specialty: Natural Language Processing <br />
*Location: Bethesda, MD, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: August 15, 2018<br />
*Contact: Dr. Andy Baxevanis, the Search Chair, <andy@mail.nih.gov><br />
<br />
The National Library of Medicine is currently recruiting for both tenure-track and tenure-eligible investigators in data science, biomedical informatics, and computational biology. <br />
Individuals with significant experience in the use of statistical, machine learning, optimization and advanced mathematical methodologies as applied to biomedical and health science are encouraged to apply. <br />
Additional details are available by following the links below. <br />
<br />
https://www.nlm.nih.gov/careers/jobopenings.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_01_20180813.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_02_20180813.html<br />
<br />
<br />
<br />
== Question-Answering Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: Question-answering <br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: July 3, 2018<br />
*Contact: Franck Dernoncourt <dernonco@adobe.com><br />
<br />
We are looking for a PhD student with background in question-answering for a late summer or autumn, ~13-week internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile).<br />
<br />
== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Natural language understanding, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The principal investigator is Prof. Sien Moens. CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world.<br />
<br />
The successful candidate will have an opportunity to work on innovative natural language understanding research such as grounding language meaning into visual perception and translating narrative language into visual events. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.<br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Perform own research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.<br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organisation of student seminars, and the supervision of bachelor and master theses. <br />
* Help in the supervision of PhD researchers of the CALCULUS team.<br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in fundamental research in language understanding and machine learning. <br />
* You are not afraid of creative and original ideas and solutions.<br />
* You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.<br />
* You are good at collaborating with and leading others.<br />
* You work proactively and independently and have good communication skills.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
* We offer a 2 x 2-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences and for short research stays.<br />
<br />
'''Interested'''<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Text mining, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data. The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners. <br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Design and develop machine learning methods for multilingual text mining. <br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses. <br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. <br />
* You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.<br />
* You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
<br />
* We offer a two-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences.<br />
<br />
'''Interested'''<br />
<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==<br />
<br />
* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: deep learning, summarization<br />
* Location: Darmstadt<br />
* Deadline: June 27, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [http://www.aiphes.tu-darmstadt.de/ Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling two positions for three years, <br />
starting as soon as possible, located in Darmstadt and associated with <br />
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
The positions provide the opportunity to obtain a doctoral degree with <br />
an emphasis in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, abstractive summarization, or a related area. <br />
Applicants should be willing to work on cross-lingual, cross-modality <br />
and domain-independent methods. Prior experience in transfer learning, <br />
multi-task learning, adversarial learning, deep reinforcement learning <br />
or related methods is a plus.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, computer vision, and data and information management <br />
will be developed. AIPHES investigates a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
benefit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. <br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning <br />
(Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). AIPHES strives to publish its results at <br />
leading <br />
scientific conferences and is actively supporting its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Machine Learning, NLP, or a related study <br />
program. We expect the ability to work independently, personal <br />
commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Prior experience in <br />
scientific work is a plus. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [https://www.ukp.tu-darmstadt.de UKP Lab] is a highly dynamic research group committed to <br />
top-level conferences, technologies of the highest standards, <br />
cooperative work style and close interaction of team members. Its <br />
BMBF-funded Centre for the Digital Foundation of Research in the <br />
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, <br />
machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a <br />
user-defined topic: neural networks determine relevant pro and con <br />
arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of <br />
the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in electronic form. Application materials must be submitted via the <br />
following form by June, 27th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
== Postdoc position: Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University<br />
*Title: Postdoctoral Researcher<br />
*Location: Milan, Italy<br />
*Deadline: June 22nd, 2018, 5 p.m. <br />
*Starting date: as early as possible, but no later than September 2018<br />
*Duration: 1 year <br />
*Date Posted: June 18, 2018<br />
*Contact: Paola Cillo (paola.cillo@unibocconi.it) <br />
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)<br />
<br />
Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.<br />
<br />
REQUIREMENTS/QUALIFICATIONS <br />
<br />
The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks. The candidate is expected to have:<br />
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.<br />
* Good programming skills in Python.<br />
* Fluent English. Knowledge of other languages is more than welcome. Knowledge of Italian is NOT a requirement.<br />
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).<br />
* Publications in top-tier venues in the field of Computational Linguistics.<br />
* Experience in Ph.D. student supervision is a plus.<br />
* Salary: 43,310.50 euros per annum<br />
<br />
HOW TO APPLY <br />
<br />
The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it <br />
You can find more information about the project and call here: https://bit.ly/2t1DnAO<br />
<br />
== Postdocs: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Postdoctoral Researcher<br />
*Location: Baltimore, MD<br />
*Deadline: Applications will be accepted until positions are filled<br />
*Date Posted: June 6, 2018<br />
*Contact: clspsearch@clsp.jhu.edu<br />
*URL: https://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.<br />
<br />
Example topics include:<br />
* Cross-lingual Information Retrieval<br />
* Trend Detection in Social Media<br />
* Social Media and Mental Health<br />
* Analysis of Clinical Medical Text<br />
* Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation<br />
* NLP and Machine Learning for Clinical Data Analysis<br />
<br />
Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.<br />
<br />
CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.<br />
<br />
Applicants are not required to be to US citizens or permanent residents.<br />
<br />
Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.<br />
<br />
Details and application information:<br />
http://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
<br />
== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==<br />
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]<br />
* Title: Research Fellow <br />
* Speciality: Software engineering, machine learning, natural language processing<br />
* Location: Tartu, Estonia<br />
* Deadline: June 4, 2018<br />
* Date posted: May 21, 2018<br />
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)<br />
<br />
'''Postdoctoral position''' <br/><br />
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.<br />
<br />
The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:<br />
<br />
* open innovation,<br />
* energy-efficient software development,<br />
* software testing.<br />
<br />
The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.<br />
<br />
'''Requirements''' <br/><br />
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.<br />
<br />
The expected start date is 1 September 2018, but a later start date can be negotiated.<br />
<br />
The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].<br />
<br />
== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==<br />
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design<br />
* Location: Albany, New York, USA <br />
* Deadline: July 31, 2018<br />
* Date posted: May 18, 2018<br />
* Contact: Tomek Strzalkowski (tomek {at} albany.edu) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* ''The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project.'' The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.<br />
* ''The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project.'' The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information. <br />
<br />
'''Requirements for the PANACEA position''' <br/><br />
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.<br />
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus. <br />
<br />
'''Requirements for the COMETH positions''' <br/><br />
For the COMETH project, we seek '''two''' postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.<br />
<br />
* The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus. <br />
* The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.<br />
<br />
'''Overall Requirements''' <br/><br />
* For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.<br />
<br />
The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.<br />
<br />
'''How to Apply''' <br/> <br />
<br />
Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu <br />
<br />
== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Two PhD positions <br />
* Speciality: Natural Language Understanding, Summarisation, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: May 31, 2018<br />
* Date posted: April 30, 2018<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Two PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.<br />
<br />
The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.<br />
<br />
This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.<br />
<br />
The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills. <br />
<br />
The successful PhD candidates will join the [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group] at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at [http://www.epfl.ch EPFL] conditional on parallel application to, and acceptance by, the [http://phd.epfl.ch/applicants EPFL Doctoral School]. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online here:<br />
[http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D]<br />
<br />
'''Idiap'''<br />
<br />
Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.<br />
<br />
<br />
<br />
== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Text mining, natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.<br />
* Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*PhD in computer science or equivalent.<br />
* Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.<br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: PhD researcher <br />
* Speciality: Natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''PhD positions''' <br/><br />
<br />
* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*Master degree in computer science or equivalent.<br />
*Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization. <br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12334Employment opportunities, postdoctoral positions, summer jobs2018-11-22T12:32:37Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
<hr />
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<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: December 15, 2018 (or until filled)<br />
* Date posted: November 22, 2018<br />
* Contact: https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PhD- or (Senior-)PostDoc level; for an initial term of two years)'''<br />
<br />
The UKP Lab is an internationally recognized research institute with about 35 team members. We work on various aspects of Natural Language Processing (NLP), with an emphasis on semantic text analysis and generation, argument mining, and interactive machine learning. Besides, we have a strong profile in deep learning for NLP, construction of large-scale benchmarks, or knowledge graphs. We collaborate with a wide range of both academic and industrial partners.<br />
<br />
We are looking for candidates in Computer Science with a specialization in Natural Language Processing, preferably with expertise in research and development projects, prior publication experience, and strong communication skills. The research topics of the position may include: NLP in low-research settings, argument mining and retrieval, multimodal content processing, privacy-enhanced NLP as well as machine learning for NLP (deep reinforcement learning, neural network architectures). The successful applicant will work on research and development as part of a team in one of the areas above. We disseminate the results in top venues of the field and as free research software and datasets. The lab offers highly attractive options for personal growth and career development at all levels of the scientific career. Upon interest, additional qualifications in teaching and project management can be acquired.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research focus "Data Science” and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals. In 2018, Darmstadt has achieved the first place in the category Cities of the Future in a ranking of German cities.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please apply under https://recruitment.ukp.informatik.tu-darmstadt.de/ukp/ by December 15, 2018. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Assistant Professor, Department of Linguistics and Translation, University of Montreal == <br />
<br />
* Employer: Department of Linguistics and Translation, University of Montreal<br />
* Title: Assistant Professor (tenure-track)<br />
* Specialty: Computational linguistics<br />
* Location: Montreal, Canada<br />
* Deadline: December 13, 2018 <br />
* Date posted: November 10, 2018 <br />
* Contact: Mireille Tremblay <mireille.tremblay.4@umontreal.ca > and https://ling-trad.umontreal.ca<br />
<br />
The Département de linguistique et de traduction is seeking applications for a full-time tenure-track position at the rank of Assistant Professor in computational linguistics/natural language processing.<br />
<br />
Responsibilities<br />
<br />
The appointed candidate will be expected to teach at all three levels of the curriculum, supervise graduate students, engage in ongoing research and publication, and contribute to the academic life and reputation of the University. This person will play an important role in the development of the “Computational Linguistics” branch of our curriculum and in establishing cross-disciplinary collaborations within and outside of the University.<br />
<br />
Requirements<br />
<br />
* Ph.D. in linguistics, computer science, or a related field.<br />
* Education in both linguistics and computer science, with a strong background in core linguistics.<br />
* Demonstrated interest in using computational techniques in the study of language.<br />
* Ability to teach in at least one of the core domains of linguistics.<br />
* Excellent publication track record in computational linguistics.<br />
* University teaching experience.<br />
* Sufficient knowledge of written and spoken French.<br />
<br />
Deadline: until December 13, 2018 inclusively<br />
<br />
Treatment: Université de Montréal offers competitive salaries and a full range of benefits.<br />
<br />
Starting date: On or after August 1st, 2019<br />
<br />
Application<br />
<br />
The application must include the following documents:<br />
* a cover letter<br />
* a curriculum vitæ<br />
* copies of recent publications and research<br />
<br />
Three letters of recommendation are also to be sent directly to the department chair by the referees.<br />
<br />
Application and letters of recommendation must be sent to the chair of the Département de linguistique et de traduction at the following address:<br />
<br />
Mireille Tremblay, directrice <br><br />
Département de linguistique et de traduction<br><br />
Faculté des arts et des sciences<br><br />
Université de Montréal<br><br />
C.P. 6128, succursale Centre-ville<br><br />
Montréal (QC) H3C 3J7<br><br />
Canada<br />
<br />
Application and letters of recommendation may also be sent by email at the following address: mireille.tremblay.4@umontreal.ca <br />
<br />
For more information about the Department, please consult its website at http://ling-trad.umontreal.ca<br />
<br />
Université de Montréal is a Québec university with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the world’s best specialists. In accordance with the institution’s language policy, Université de Montréal provides support for newly-recruited faculty to attain proficiency in French.<br />
<br />
The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview.<br />
<br />
Through its Equal Access Employment Program, Université de Montréal invites women, Aboriginal people, visible and ethnical minorities, as well as persons with disabilities to apply. During the recruitment process, our selection tools will be adapted to meet the needs of people with disabilities who request it. Be assured of the confidentiality of this information.<br />
<br />
Université de Montréal is committed to the inclusion and the diversity of its staff and also encourages people of all sexual and gender identities to apply.<br />
<br />
We invite all qualified candidates to apply at UdeM. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents.<br />
<br />
<br />
<br />
== Software Engineer for Text Mining Applications at the University of Manchester == <br />
<br />
* Employer: National Centre for Text Mining, School of Computer Science, University of Manchester<br />
* Title: Software Engineer<br />
* Specialty: Text Mining<br />
* Location: Manchester, UK<br />
* Deadline: November 25, 2018 <br />
* Date posted: October 25, 2018 <br />
* Contact: Sophia Ananiadou <sophia.ananiadou@manchester.ac.uk> <br />
<br />
Applications are invited for a Software Engineer post (full time) for a period of 5 years<br />
<br />
The successful candidate will be part of the National Centre for Text Mining (http://www.nactem.ac.uk/) which is hosted by the School of Computer Science, joining a strong and dynamic team in text mining. The National Centre for Text Mining provides next-generation text mining services to the community. We use natural language processing techniques to build advanced search systems in a number of domains. We are seeking a self-motivated, creative and experienced software engineer (must have substantive post graduation experience) to enhance our team expertise particularly in the areas of wrapping text mining analysis workflows, software development for search engines bringing the benefits of text mining to end users, Web services, integrating text mining with knowledge bases, cloud deployment of services and advanced user interfaces.<br />
<br />
Essential skills and experience include: Linux/unix, extensive experience of software design and development gained in a professional software development environment, experience of producing distributed solutions and of working with large datasets, Java or C++ with XML technologies, REST/SOAP Web services, knowledge of cloud/cluster computing/SaaS/PaaS, Maven.<br />
<br />
* Salary : £40,792 to £50,132 per annum dependent upon experience<br />
* Hours Per week: Full Time<br />
* Contract Duration : Starting 1 January 2019 for 5 years <br />
<br />
Further details: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=16308<br />
<br />
<br />
== Assistant Professor, Department of Linguistics, University of Florida == <br />
<br />
* Employer: Department of Linguistics, University of Florida<br />
* Title: Tenure-track Assistant Professor<br />
* Specialty: computational language science<br />
* Location: Gainesville, FL 32601<br />
* Deadline: November 18, 2018 <br />
* Date posted: October 18, 2018 <br />
* Contact: Stefanie Wulff <swulff@ufl.edu> and https://apply.interfolio.com/56557<br />
<br />
The University of Florida invites applications for a tenure-track appointment in computational language science at the rank of assistant professor, effective August 16, 2019. This is a 9-month position. Applicants are expected to have a Ph.D. in linguistics, computer science, or a closely-related field. Candidates should have an active research agenda studying language from a computational perspective. Specialization is open, including but not limited to sociolinguistics, neuro/psycholinguistics, corpus linguistics, and/or language documentation. UF Linguistics seeks to train the next generation of linguists who are comfortable integrating and evaluating computational approaches in their research. To this end, ability to teach computationally-oriented courses is required. Candidates must hold the Ph.D. by the starting date.<br />
<br />
The successful candidate will be expected to 1) maintain an active research agenda, 2) pursue external research funding, 3) teach two courses per semester at the undergraduate and/or graduate level, 4) provide service to the department, the university, and the profession, and 5) seek collaborations within the department as well as with other units on campus such as the UF Data Science and Information Technology Center, the UF Informatics Institute, or the McKnight Brain Institute.<br />
<br />
The Department is committed to creating an environment that affirms diversity and inclusion across a variety of dimensions, including ability, class, ethnicity/race, religion and/or cultural background, gender identity and expression. We particularly welcome applicants who can contribute to such an environment through their scholarship, teaching, mentoring, and professional service. The university and greater Gainesville community enjoy a diversity of cultural events, restaurants, year-round outdoor recreational activities, and social opportunities<br />
<br />
Salary is competitive, commensurate with qualifications and experience, and includes a full benefits package.<br />
<br />
The Linguistics Department at the University of Florida is a vibrant and congenial unit consisting of 11 full-time faculty and 15 affiliated faculty in the departments of Anthropology; Languages, Literatures, and Cultures; Spanish and Portuguese; and the Dial Center for Written & Oral Communication. We offer a B.A., M.A. and Ph.D. in Linguistics, as well as an undergraduate minor and undergraduate certificate in TESL and a graduate certificate in Second Language Acquisition and Teaching. We have faculty expertise in a wide range of linguistic subfields, and particular strengths in the areas of bilingualism, language documentation, psycholinguistics, sociolinguistics, and African linguistics. Please see our website, lin.ufl.edu, for more information about the department.<br />
<br />
For full consideration, applications must be submitted online at https://apply.interfolio.com/56557 and must include: (1) a brief cover letter, (2) a statement of teaching and research interests, (3) a CV, (4) 1-3 sample publications, (5) the names and email addresses for three references, and (6) representative teaching evaluations if available. After initial review, letters of recommendation will be requested for selected applicants. Review of applications will begin on 18 November 2018 and will continue until the position is filled.<br />
<br />
All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.<br />
<br />
The final candidate will be required to provide an official transcript to the department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.<br />
<br />
The University of Florida is an Equal Opportunity Employer dedicated to building a broadly diverse and inclusive faculty and staff. The University of Florida invites all qualified applicants, including minorities, women, veterans, and individuals with disabilities to apply. The University of Florida is a public institution and subject to all requirements under Florida Sunshine and Public Record laws.<br />
<br />
== Postdoctoral Researcher, Cognitive AI Lab, University of Arizona ==<br />
<br />
* Employer: School of Information, University of Arizona<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: natural language processing<br />
* Location: Tucson, AZ, USA<br />
* Deadline: Open until filled<br />
* Date posted: October 15, 2018<br />
* Contact: Peter Jansen <pajansen@email.arizona.edu><br />
<br />
Postdoctoral Research Associate I <br /><br />
https://uacareers.com/postings/31213 <br />
<br />
Position Summary <br /><br />
The Cognitive Artificial Intelligence Laboratory ( http://www.cognitiveai.org ) in the School of Information at the University of Arizona invites applications for a Postdoctoral Research Associate for projects specializing in natural language processing and explanation-centered inference.<br />
<br />
Natural language processing systems are steadily increasing performance on inference tasks like question answering, but few systems are able to provide explanations describing why their answers are correct. These explanations are critical in domains like science or medicine, where user trust is paramount and the cost of making errors is high. Our work has shown that one of the main barriers to increasing inference and explanation capability is the ability to combine information – for example, elementary science questions generally require combining between 6 and 12 different facts to answer and explain, but state-of-the-art systems generally struggle integrating more than two facts together. The successful candidate will combine novel methods in data collection, annotation, representation, and algorithmic development to exceed this limitation in combining information, and apply these methods to answering and explaining science questions. <br />
<br />
A talk on our recent work in this area is available here: https://www.youtube.com/watch?v=EneqL2sr6cQ<br />
<br />
Minimum Qualifications<br />
* A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.<br />
* Demonstrated interest in natural language processing or machine learning techniques.<br />
* Excellent verbal and written communication skills<br />
<br />
Duties and Responsibilities<br />
* Engage in innovative natural language processing research<br />
* Write and publish scientific articles describing methods and findings in high-quality venues (e.g. ACL, EMNLP, NAACL, etc.)<br />
* Assist in mentoring graduate and undergraduate students, and the management of ongoing projects<br />
* Support writing grant proposals for external funding opportunities<br />
* Serve as a collaborative member of a team of interdisciplinary researchers<br />
<br />
Preferred Qualifications<br />
* Knowledge of computational approaches to semantic knowledge representation, graph-based inference, and/or rule-based systems<br />
* Strong scholarly writing skills and publication record<br />
<br />
Full Posting/To Apply <br /><br />
https://uacareers.com/postings/31213<br />
<br />
== Temporary lecturer, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Lecturer<br />
* Specialty: computational linguistics and/or natural language processing and general linguistics<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: October 24, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01317<br />
<br />
The Department of Linguistics at the University of California, Santa Barbara invites applications for a qualified temporary Lecturer to teach course(s) in computational linguistics and potentially general linguistics. To learn more about the department, see: http://www.linguistics.ucsb.edu/<br />
<br />
The Lecturer will teach an advanced undergraduate course in computational linguistics in the Winter 2019 or Spring 2019 quarter. The successful candidate may also have the opportunity to teach other courses that support the department’s undergraduate programs, including classes currently listed in the UCSB general catalog and/or special-topic courses proposed by the applicant; these courses may be offered in Winter 2019 or Spring 2019.<br />
<br />
Applicants must possess a Master’s Degree in Linguistics and have at least one year teaching college-level linguistics courses. A Ph.D. in Linguistics is preferred but not required. The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
To apply, please go to the following link: https://recruit.ap.ucsb.edu/apply/JPF01317. Applicants should submit a curriculum vitae and a cover letter stating their qualifications for teaching computational linguistics as well as any additional courses they may be interested in teaching. Applicants should also provide contact information for three references. To ensure full consideration, all application materials should be received by 10/24/18; however, the position is open until filled. <br />
<br />
The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Assistant Professor, Department of Linguistics, University of California, Santa Barbara ==<br />
<br />
* Employer: Department of Linguistics, University of California, Santa Barbara<br />
* Title: Assistant Professor<br />
* Specialty: computational linguistics and/or natural language processing<br />
* Location: Santa Barbara, CA 93106<br />
* Deadline: November 9, 2018<br />
* Date posted: September 27, 2018<br />
* Contact: https://recruit.ap.ucsb.edu/apply/JPF01310 and complingsearch@linguistics.ucsb.edu<br />
<br />
The Linguistics Department of the University of California, Santa Barbara seeks to hire a linguist who is a specialist in computational linguistics and/or natural language processing. The appointment will be a tenure-track position at the Assistant Professor level, effective July 1, 2019.<br />
<br />
The successful candidate will have an active research program in computational linguistics and/or natural language processing and will have a record of participation in the computational linguistics/NLP community. Proven expertise in machine learning including word embeddings/vector space semantics is required, as is expertise in using computational linguistics methods to address theoretical and/or applied questions. Capacity to engage with the distinctive theoretical orientation of the department is expected. We welcome applicants with the ability to contribute to departmental foci, such as corpus linguistics, language and cognition, language acquisition, and/or less studied languages. We also encourage applicants who have the potential to interact with colleagues and students across disciplinary boundaries at UCSB.<br />
<br />
The successful candidate will demonstrate commitment to and ability in graduate and undergraduate teaching and will be expected to teach a range of graduate and undergraduate courses in computational linguistics, including those with relevance to industry, as well as to contribute to the department’s undergraduate major with an emphasis in Language and Speech Technologies. For more information on the department, see www.linguistics.ucsb.edu.<br />
<br />
The minimum requirement to be considered as an applicant is the completion of all requirements for a Ph.D. in linguistics or a closely-related field except the dissertation (or equivalent) at the time of application. A Ph.D. in linguistics or a closely-related field is expected by the time of appointment. Review of applications will begin after Friday, November 9, 2018. The position will remain open until filled. <br />
<br />
Applicants must complete the online form at https://recruit.ap.ucsb.edu/apply/JPF01310 and must submit online the following in PDF format: letter of application, statement of research interests, teaching statement, curriculum vitae, and 2 writing samples. Applicants are also encouraged to submit an optional statement on contributions to diversity. <br />
<br />
Applicants should request 3-5 letters of reference to be sent directly to https://recruit.ap.ucsb.edu/reference. Inquiries may be addressed to the Search Committee at complingsearch@linguistics.ucsb.edu. Initial screening of selected applicants will be conducted via Zoom. Our department has a genuine commitment to diversity, and is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service.<br />
<br />
The University of California is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.<br />
<br />
== Postdoctoral Fellow, Quantitative Criticism Lab, University of Texas at Austin ==<br />
<br />
* Employer: Quantitative Criticism Lab, University of Texas at Austin<br />
* Title: Postdoctoral Fellow<br />
* Specialty: Digital humanities and natural language processing<br />
* Location: Austin, TX or remote<br />
* Deadline: October 15, 2018<br />
* Date posted: September 7, 2018<br />
* Contact: https://www.nature.com/naturejobs/science/jobs/652327-postdoctoral-fellow<br />
<br />
The Quantitative Criticism Lab (QCL; https://www.qcrit.org), a research group developing cross-disciplinary approaches to the study of literature and culture, invites applications for a full-time postdoctoral fellowship. The duration of the fellowship is 18 months, from January 2, 2019 to June 30, 2020. The field of specialization is open, but expertise in computer programming and statistical analysis is essential, as is a deep interest in the study of literature. QCL’s physical lab space is based at The University of Texas at Austin; residence in Austin during the fellowship period is preferred but not required. The fellow will have no teaching responsibilities. The position is funded by a Digital Extension Grant from the American Council of Learned Societies (ACLS).<br />
<br />
The ACLS-funded project will produce a web-based suite of tools for traditionally-trained humanists to analyze literary texts in a quantitative manner. The tools are designed with an important class of literary problems in mind, exemplified by the identification of verbal parallels and, at a larger scale, by the individuating of entire works within generic traditions. We take two main approaches: sequence alignment for the detection of verbal resemblance, and stylometry augmented by machine learning for the profiling of texts and corpora. The tools are expected both to enhance traditional modes of literary criticism and to enable novel quantitative analyses of the cultural evolution of literature.<br />
<br />
The postdoctoral fellow’s primary responsibilities will be to lead development of these tools and to participate in other aspects of QCL’s research program according to background and interests. The work will involve coding, research design, data analysis, literary criticism, and scholarly writing for diverse venues, as well as various organizational duties related to workshops and conferences. The postdoctoral fellow will work under the supervision of Pramit Chaudhuri (UT Austin) and Joseph Dexter (Dartmouth College), the co-directors of QCL, and will collaborate with a diverse array of scholars, in both academia and industry, affiliated with QCL. In addition, the fellow will be expected to play a major role in mentoring the numerous graduate, undergraduate, and high school students who conduct research with QCL.<br />
<br />
A Ph.D. in a computational, statistical, linguistic, or literary field is required. Possible disciplines include (but are not limited to) anthropology, applied mathematics, bioinformatics, classics, comparative literature, computer science, English, evolutionary biology, linguistics, and statistics. Prior experience with any of the following areas is highly desirable but not required: computational linguistics, cultural evolution, digital humanities, literary criticism of a premodern or non-Anglophone tradition (especially Latin or Ancient Greek), machine learning, and natural language processing. By the start date of the position, applicants should either have the Ph.D. in hand or be able to provide certification from their home institution that all degree requirements have been fulfilled. Applicants must have received the Ph.D. within the last three years.<br />
<br />
For full consideration, applicants should submit the following materials by October 15, 2018:<br />
<br />
# CV;<br />
# Cover letter;<br />
# Short (2-4 page) summary of past and current research interests, giving particular attention to any computational work;<br />
# Writing sample of no more than 40 pages (e.g., article or dissertation chapter).<br />
<br />
In addition, applicants should arrange to have three letters of recommendation forwarded by the deadline. Please submit your CV and cover letter on the UT Jobs website: https://utdirect.utexas.edu/apps/hr/jobs/nlogon/180823010712. Please submit the additional materials via email to vnoya@austin.utexas.edu. Questions can be directed to Vanessa Noya at the same address.<br />
<br />
The salary will be $48,000 per year, plus benefits.<br />
<br />
The successful candidate must be able to begin work in this position by January 2, 2019.<br />
<br />
A criminal history background check will be required for finalist(s) under consideration for this position.<br />
<br />
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.<br />
<br />
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.<br />
<br />
If hired, you will be required to complete the federal Employment Eligibility Verification form, I-9. You will be required to present acceptable, original documents (https://hr.utexas.edu/current/services/employment-eligibility-verification-i9-docs) to prove your identity and authorization to work in the United States. Information from the documents will be submitted to the federal E-Verify system for verification. Documents must be presented no later than the third day of employment. Failure to do so will result in dismissal.<br />
<br />
UT Austin is a Tobacco-free Campus (http://tobaccofree.utexas.edu/). <br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: September 30, 2018 (or until filled)<br />
* Date posted: September 6, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities. <br />
<br />
Possible areas of research include, but are not limited to:<br />
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;<br />
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;<br />
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;<br />
* joint text and image processing for content classification in social media, e.g. identifying bias;<br />
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.<br />
<br />
The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.<br />
<br />
We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab. <br />
<br />
The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining. UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Tenure-track and tenure-eligible investigators at the National Library of Medicine, Bethesda, Maryland ==<br />
*Employer: National Library of Medicine<br />
*Title: Tenure-track and tenure-eligible investigators <br />
*Specialty: Natural Language Processing <br />
*Location: Bethesda, MD, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: August 15, 2018<br />
*Contact: Dr. Andy Baxevanis, the Search Chair, <andy@mail.nih.gov><br />
<br />
The National Library of Medicine is currently recruiting for both tenure-track and tenure-eligible investigators in data science, biomedical informatics, and computational biology. <br />
Individuals with significant experience in the use of statistical, machine learning, optimization and advanced mathematical methodologies as applied to biomedical and health science are encouraged to apply. <br />
Additional details are available by following the links below. <br />
<br />
https://www.nlm.nih.gov/careers/jobopenings.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_01_20180813.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_02_20180813.html<br />
<br />
<br />
<br />
== Question-Answering Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: Question-answering <br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: July 3, 2018<br />
*Contact: Franck Dernoncourt <dernonco@adobe.com><br />
<br />
We are looking for a PhD student with background in question-answering for a late summer or autumn, ~13-week internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile).<br />
<br />
== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Natural language understanding, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The principal investigator is Prof. Sien Moens. CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world.<br />
<br />
The successful candidate will have an opportunity to work on innovative natural language understanding research such as grounding language meaning into visual perception and translating narrative language into visual events. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.<br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Perform own research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.<br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organisation of student seminars, and the supervision of bachelor and master theses. <br />
* Help in the supervision of PhD researchers of the CALCULUS team.<br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in fundamental research in language understanding and machine learning. <br />
* You are not afraid of creative and original ideas and solutions.<br />
* You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.<br />
* You are good at collaborating with and leading others.<br />
* You work proactively and independently and have good communication skills.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
* We offer a 2 x 2-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences and for short research stays.<br />
<br />
'''Interested'''<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Text mining, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data. The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners. <br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Design and develop machine learning methods for multilingual text mining. <br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses. <br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. <br />
* You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.<br />
* You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
<br />
* We offer a two-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences.<br />
<br />
'''Interested'''<br />
<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==<br />
<br />
* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: deep learning, summarization<br />
* Location: Darmstadt<br />
* Deadline: June 27, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [http://www.aiphes.tu-darmstadt.de/ Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling two positions for three years, <br />
starting as soon as possible, located in Darmstadt and associated with <br />
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
The positions provide the opportunity to obtain a doctoral degree with <br />
an emphasis in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, abstractive summarization, or a related area. <br />
Applicants should be willing to work on cross-lingual, cross-modality <br />
and domain-independent methods. Prior experience in transfer learning, <br />
multi-task learning, adversarial learning, deep reinforcement learning <br />
or related methods is a plus.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, computer vision, and data and information management <br />
will be developed. AIPHES investigates a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
benefit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. <br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning <br />
(Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). AIPHES strives to publish its results at <br />
leading <br />
scientific conferences and is actively supporting its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Machine Learning, NLP, or a related study <br />
program. We expect the ability to work independently, personal <br />
commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Prior experience in <br />
scientific work is a plus. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [https://www.ukp.tu-darmstadt.de UKP Lab] is a highly dynamic research group committed to <br />
top-level conferences, technologies of the highest standards, <br />
cooperative work style and close interaction of team members. Its <br />
BMBF-funded Centre for the Digital Foundation of Research in the <br />
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, <br />
machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a <br />
user-defined topic: neural networks determine relevant pro and con <br />
arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of <br />
the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in electronic form. Application materials must be submitted via the <br />
following form by June, 27th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
== Postdoc position: Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University<br />
*Title: Postdoctoral Researcher<br />
*Location: Milan, Italy<br />
*Deadline: June 22nd, 2018, 5 p.m. <br />
*Starting date: as early as possible, but no later than September 2018<br />
*Duration: 1 year <br />
*Date Posted: June 18, 2018<br />
*Contact: Paola Cillo (paola.cillo@unibocconi.it) <br />
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)<br />
<br />
Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.<br />
<br />
REQUIREMENTS/QUALIFICATIONS <br />
<br />
The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks. The candidate is expected to have:<br />
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.<br />
* Good programming skills in Python.<br />
* Fluent English. Knowledge of other languages is more than welcome. Knowledge of Italian is NOT a requirement.<br />
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).<br />
* Publications in top-tier venues in the field of Computational Linguistics.<br />
* Experience in Ph.D. student supervision is a plus.<br />
* Salary: 43,310.50 euros per annum<br />
<br />
HOW TO APPLY <br />
<br />
The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it <br />
You can find more information about the project and call here: https://bit.ly/2t1DnAO<br />
<br />
== Postdocs: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Postdoctoral Researcher<br />
*Location: Baltimore, MD<br />
*Deadline: Applications will be accepted until positions are filled<br />
*Date Posted: June 6, 2018<br />
*Contact: clspsearch@clsp.jhu.edu<br />
*URL: https://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.<br />
<br />
Example topics include:<br />
* Cross-lingual Information Retrieval<br />
* Trend Detection in Social Media<br />
* Social Media and Mental Health<br />
* Analysis of Clinical Medical Text<br />
* Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation<br />
* NLP and Machine Learning for Clinical Data Analysis<br />
<br />
Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.<br />
<br />
CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.<br />
<br />
Applicants are not required to be to US citizens or permanent residents.<br />
<br />
Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.<br />
<br />
Details and application information:<br />
http://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
<br />
== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==<br />
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]<br />
* Title: Research Fellow <br />
* Speciality: Software engineering, machine learning, natural language processing<br />
* Location: Tartu, Estonia<br />
* Deadline: June 4, 2018<br />
* Date posted: May 21, 2018<br />
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)<br />
<br />
'''Postdoctoral position''' <br/><br />
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.<br />
<br />
The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:<br />
<br />
* open innovation,<br />
* energy-efficient software development,<br />
* software testing.<br />
<br />
The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.<br />
<br />
'''Requirements''' <br/><br />
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.<br />
<br />
The expected start date is 1 September 2018, but a later start date can be negotiated.<br />
<br />
The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].<br />
<br />
== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==<br />
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design<br />
* Location: Albany, New York, USA <br />
* Deadline: July 31, 2018<br />
* Date posted: May 18, 2018<br />
* Contact: Tomek Strzalkowski (tomek {at} albany.edu) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* ''The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project.'' The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.<br />
* ''The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project.'' The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information. <br />
<br />
'''Requirements for the PANACEA position''' <br/><br />
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.<br />
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus. <br />
<br />
'''Requirements for the COMETH positions''' <br/><br />
For the COMETH project, we seek '''two''' postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.<br />
<br />
* The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus. <br />
* The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.<br />
<br />
'''Overall Requirements''' <br/><br />
* For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.<br />
<br />
The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.<br />
<br />
'''How to Apply''' <br/> <br />
<br />
Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu <br />
<br />
== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Two PhD positions <br />
* Speciality: Natural Language Understanding, Summarisation, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: May 31, 2018<br />
* Date posted: April 30, 2018<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Two PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.<br />
<br />
The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.<br />
<br />
This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.<br />
<br />
The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills. <br />
<br />
The successful PhD candidates will join the [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group] at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at [http://www.epfl.ch EPFL] conditional on parallel application to, and acceptance by, the [http://phd.epfl.ch/applicants EPFL Doctoral School]. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online here:<br />
[http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D]<br />
<br />
'''Idiap'''<br />
<br />
Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.<br />
<br />
<br />
<br />
== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Text mining, natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.<br />
* Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*PhD in computer science or equivalent.<br />
* Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.<br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: PhD researcher <br />
* Speciality: Natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''PhD positions''' <br/><br />
<br />
* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*Master degree in computer science or equivalent.<br />
*Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization. <br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=User:Tristan_Miller&diff=12287User:Tristan Miller2018-09-06T14:01:52Z<p>Tristan Miller: update biography</p>
<hr />
<div>I am a senior postdoctoral researcher at the Ubiquitous Knowledge Processing Lab (UKP) at Technische Universität Darmstadt. My research interests include lexical semantics, argument mining, and computational humour.<br />
<br />
I hold a B.Sc. Hons. in Computer Science from the University of Regina, an M.Sc. in Computer Science from the University of Toronto, and a Dr.-Ing. in Computer Science from Technische Universität Darmstadt.<br />
<br />
My hobbies include regicide, collecting those little tiny hangers that come with new pairs of socks, and writing brief but patently false autobiographies. For further information, please visit my personal website: https://logological.org/</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12286Employment opportunities, postdoctoral positions, summer jobs2018-09-06T13:58:38Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
<hr />
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== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Natural language processing<br />
* Location: Darmstadt<br />
* Deadline: September 30, 2018 (or until filled)<br />
* Date posted: September 6, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [https://www.ukp.tu-darmstadt.de/ Ubiquitous Knowledge Processing (UKP) Lab] at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities. <br />
<br />
Possible areas of research include, but are not limited to:<br />
* interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;<br />
* NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;<br />
* interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;<br />
* joint text and image processing for content classification in social media, e.g. identifying bias;<br />
* analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.<br />
<br />
The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.<br />
<br />
We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab. <br />
<br />
The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining. UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Tenure-track and tenure-eligible investigators at the National Library of Medicine, Bethesda, Maryland ==<br />
*Employer: National Library of Medicine<br />
*Title: Tenure-track and tenure-eligible investigators <br />
*Specialty: Natural Language Processing <br />
*Location: Bethesda, MD, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: August 15, 2018<br />
*Contact: Dr. Andy Baxevanis, the Search Chair, <andy@mail.nih.gov><br />
<br />
The National Library of Medicine is currently recruiting for both tenure-track and tenure-eligible investigators in data science, biomedical informatics, and computational biology. <br />
Individuals with significant experience in the use of statistical, machine learning, optimization and advanced mathematical methodologies as applied to biomedical and health science are encouraged to apply. <br />
Additional details are available by following the links below. <br />
<br />
https://www.nlm.nih.gov/careers/jobopenings.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_01_20180813.html<br />
https://www.nlm.nih.gov/careers/jobopening_ncbi_02_20180813.html<br />
<br />
<br />
<br />
== Question-Answering Research Internship at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Research<br />
*Title: Research Scientist Intern <br />
*Speciality: Question-answering <br />
*Location: San Jose, CA, USA<br />
*Deadline: Applications will be accepted until the position is filled.<br />
*Date posted: July 3, 2018<br />
*Contact: Franck Dernoncourt <dernonco@adobe.com><br />
<br />
We are looking for a PhD student with background in question-answering for a late summer or autumn, ~13-week internship (starting date and length are flexible). We strongly encourage our interns to publish their work to NLP/ML conferences/journals, and as a result we prefer candidates with a strong publication record. International PhD students are welcome to apply. Highly competitive salary. To apply, please send me an email with your CV (e.g., PDF or LinkedIn) as well as the list of your publications (e.g., PDF or link to your Google Scholar profile).<br />
<br />
== Postdoctoral position in natural language understanding, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Natural language understanding, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position (extendable to four years) funded by the ERC (European Research Council) Advanced Grant CALCULUS “Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding” (http://calculus-project.eu). The principal investigator is Prof. Sien Moens. CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world.<br />
<br />
The successful candidate will have an opportunity to work on innovative natural language understanding research such as grounding language meaning into visual perception and translating narrative language into visual events. He or she will be given the opportunity for personal development beyond research, for example by contributing to teaching (e.g., at the undergraduate and graduate levels). For an outstanding candidate there is the potential to grow into an assistant professorship.<br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Perform own research in language understanding and novel machine learning paradigms in the frame of the CALCULUS project.<br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organisation of student seminars, and the supervision of bachelor and master theses. <br />
* Help in the supervision of PhD researchers of the CALCULUS team.<br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in fundamental research in language understanding and machine learning. <br />
* You are not afraid of creative and original ideas and solutions.<br />
* You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in relevant journals with high impact factor.<br />
* You are good at collaborating with and leading others.<br />
* You work proactively and independently and have good communication skills.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
* We offer a 2 x 2-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences and for short research stays.<br />
<br />
'''Interested'''<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Postdoctoral position in multilingual text mining, KU Leuven, Belgium ==<br />
<br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral researcher<br />
* Specialty: Text mining, machine learning <br />
* Location: Leuven, Belgium<br />
* Deadline: July 31, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: sien.moens@cs.kuleuven.be<br />
<br />
We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data. The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners. <br />
<br />
<br />
'''Responsibilities'''<br />
<br />
* Design and develop machine learning methods for multilingual text mining. <br />
* Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses. <br />
<br />
'''Prerequisites'''<br />
<br />
* You have (or are near completion of) a PhD in Computer Science (or a related field). <br />
* You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. <br />
* You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.<br />
* You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.<br />
* You have a very good knowledge of English, both spoken and written.<br />
* You are highly motivated, ambitious and result-oriented.<br />
<br />
'''Offer'''<br />
<br />
* We offer a two-year postdoctoral position, starting in September 2018 (negotiable).<br />
* We offer a competitive wage and yearly budget to attend conferences.<br />
<br />
'''Interested'''<br />
<br />
If interested, send your CV including publication list, motivation letter and two recommendation letters by e-mail to Prof. dr. Sien Moens (sien.moens@cs.kuleuven.be) as soon as possible and the latest by July 31, 2018. For more information please contact Prof. dr. Sien Moens: tel.: +32 16 32 53 83. Excellent candidates will be invited for an interview (possibly via Skype).<br />
<br />
'''The research team'''<br />
<br />
The Language Intelligence & Information Retrieval (LIIR) lab (https://liir.cs.kuleuven.be) of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.<br />
<br />
'''The university'''<br />
<br />
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==<br />
<br />
* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: deep learning, summarization<br />
* Location: Darmstadt<br />
* Deadline: June 27, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [http://www.aiphes.tu-darmstadt.de/ Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling two positions for three years, <br />
starting as soon as possible, located in Darmstadt and associated with <br />
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
The positions provide the opportunity to obtain a doctoral degree with <br />
an emphasis in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, abstractive summarization, or a related area. <br />
Applicants should be willing to work on cross-lingual, cross-modality <br />
and domain-independent methods. Prior experience in transfer learning, <br />
multi-task learning, adversarial learning, deep reinforcement learning <br />
or related methods is a plus.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, computer vision, and data and information management <br />
will be developed. AIPHES investigates a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
benefit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. <br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning <br />
(Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). AIPHES strives to publish its results at <br />
leading <br />
scientific conferences and is actively supporting its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Machine Learning, NLP, or a related study <br />
program. We expect the ability to work independently, personal <br />
commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Prior experience in <br />
scientific work is a plus. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [https://www.ukp.tu-darmstadt.de UKP Lab] is a highly dynamic research group committed to <br />
top-level conferences, technologies of the highest standards, <br />
cooperative work style and close interaction of team members. Its <br />
BMBF-funded Centre for the Digital Foundation of Research in the <br />
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, <br />
machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a <br />
user-defined topic: neural networks determine relevant pro and con <br />
arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of <br />
the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in electronic form. Application materials must be submitted via the <br />
following form by June, 27th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
== Postdoc position: Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University<br />
*Title: Postdoctoral Researcher<br />
*Location: Milan, Italy<br />
*Deadline: June 22nd, 2018, 5 p.m. <br />
*Starting date: as early as possible, but no later than September 2018<br />
*Duration: 1 year <br />
*Date Posted: June 18, 2018<br />
*Contact: Paola Cillo (paola.cillo@unibocconi.it) <br />
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)<br />
<br />
Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.<br />
<br />
REQUIREMENTS/QUALIFICATIONS <br />
<br />
The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks. The candidate is expected to have:<br />
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.<br />
* Good programming skills in Python.<br />
* Fluent English. Knowledge of other languages is more than welcome. Knowledge of Italian is NOT a requirement.<br />
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).<br />
* Publications in top-tier venues in the field of Computational Linguistics.<br />
* Experience in Ph.D. student supervision is a plus.<br />
* Salary: 43,310.50 euros per annum<br />
<br />
HOW TO APPLY <br />
<br />
The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it <br />
You can find more information about the project and call here: https://bit.ly/2t1DnAO<br />
<br />
== Postdocs: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Postdoctoral Researcher<br />
*Location: Baltimore, MD<br />
*Deadline: Applications will be accepted until positions are filled<br />
*Date Posted: June 6, 2018<br />
*Contact: clspsearch@clsp.jhu.edu<br />
*URL: https://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.<br />
<br />
Example topics include:<br />
* Cross-lingual Information Retrieval<br />
* Trend Detection in Social Media<br />
* Social Media and Mental Health<br />
* Analysis of Clinical Medical Text<br />
* Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation<br />
* NLP and Machine Learning for Clinical Data Analysis<br />
<br />
Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.<br />
<br />
CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.<br />
<br />
Applicants are not required to be to US citizens or permanent residents.<br />
<br />
Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.<br />
<br />
Details and application information:<br />
http://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
<br />
== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==<br />
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]<br />
* Title: Research Fellow <br />
* Speciality: Software engineering, machine learning, natural language processing<br />
* Location: Tartu, Estonia<br />
* Deadline: June 4, 2018<br />
* Date posted: May 21, 2018<br />
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)<br />
<br />
'''Postdoctoral position''' <br/><br />
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.<br />
<br />
The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:<br />
<br />
* open innovation,<br />
* energy-efficient software development,<br />
* software testing.<br />
<br />
The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.<br />
<br />
'''Requirements''' <br/><br />
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.<br />
<br />
The expected start date is 1 September 2018, but a later start date can be negotiated.<br />
<br />
The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].<br />
<br />
== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==<br />
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design<br />
* Location: Albany, New York, USA <br />
* Deadline: July 31, 2018<br />
* Date posted: May 18, 2018<br />
* Contact: Tomek Strzalkowski (tomek {at} albany.edu) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* ''The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project.'' The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.<br />
* ''The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project.'' The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information. <br />
<br />
'''Requirements for the PANACEA position''' <br/><br />
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.<br />
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus. <br />
<br />
'''Requirements for the COMETH positions''' <br/><br />
For the COMETH project, we seek '''two''' postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.<br />
<br />
* The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus. <br />
* The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.<br />
<br />
'''Overall Requirements''' <br/><br />
* For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.<br />
<br />
The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.<br />
<br />
'''How to Apply''' <br/> <br />
<br />
Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu <br />
<br />
== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Two PhD positions <br />
* Speciality: Natural Language Understanding, Summarisation, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: May 31, 2018<br />
* Date posted: April 30, 2018<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Two PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.<br />
<br />
The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.<br />
<br />
This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.<br />
<br />
The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills. <br />
<br />
The successful PhD candidates will join the [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group] at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at [http://www.epfl.ch EPFL] conditional on parallel application to, and acceptance by, the [http://phd.epfl.ch/applicants EPFL Doctoral School]. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online here:<br />
[http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D]<br />
<br />
'''Idiap'''<br />
<br />
Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.<br />
<br />
<br />
<br />
== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Text mining, natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.<br />
* Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*PhD in computer science or equivalent.<br />
* Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.<br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: PhD researcher <br />
* Speciality: Natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''PhD positions''' <br/><br />
<br />
* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*Master degree in computer science or equivalent.<br />
*Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization. <br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12256Employment opportunities, postdoctoral positions, summer jobs2018-06-18T09:31:58Z<p>Tristan Miller: PhD positions in DFG Graduate School AIPHES, TU Darmstadt</p>
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<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt ==<br />
<br />
* Employer: [https://www.aiphes.tu-darmstadt.de/ DFG Graduate School AIPHES], [https://www.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: deep learning, summarization<br />
* Location: Darmstadt<br />
* Deadline: June 27, 2018<br />
* Date posted: June 18, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The [http://www.aiphes.tu-darmstadt.de/ Research Training Group “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling two positions for three years, <br />
starting as soon as possible, located in Darmstadt and associated with <br />
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
The positions provide the opportunity to obtain a doctoral degree with <br />
an emphasis in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, abstractive summarization, or a related area. <br />
Applicants should be willing to work on cross-lingual, cross-modality <br />
and domain-independent methods. Prior experience in transfer learning, <br />
multi-task learning, adversarial learning, deep reinforcement learning <br />
or related methods is a plus.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, computer vision, and data and information management <br />
will be developed. AIPHES investigates a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
benefit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. <br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning <br />
(Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). AIPHES strives to publish its results at <br />
leading <br />
scientific conferences and is actively supporting its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Machine Learning, NLP, or a related study <br />
program. We expect the ability to work independently, personal <br />
commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Prior experience in <br />
scientific work is a plus. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [https://www.ukp.tu-darmstadt.de UKP Lab] is a highly dynamic research group committed to <br />
top-level conferences, technologies of the highest standards, <br />
cooperative work style and close interaction of team members. Its <br />
BMBF-funded Centre for the Digital Foundation of Research in the <br />
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, <br />
machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a <br />
user-defined topic: neural networks determine relevant pro and con <br />
arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of <br />
the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in electronic form. Application materials must be submitted via the <br />
following form by June, 27th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
== Postdoc position: Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University<br />
*Title: Postdoctoral Researcher<br />
*Location: Milan, Italy<br />
*Deadline: June 22nd, 2018, 5 p.m. <br />
*Starting date: as early as possible, but no later than September 2018<br />
*Duration: 1 year <br />
*Date Posted: June 18, 2018<br />
*Contact: Paola Cillo (paola.cillo@unibocconi.it) <br />
*URL: https://bit.ly/2JW2tKZ (select the Gucci Lab call)<br />
<br />
Gucci Research Lab (GRL) is a unique partnership between Bocconi University and Gucci to identify and study the trends that define the way in which organizations are evolving. This position is part of a larger project by the Gucci Lab at Bocconi on the effects of a change in a firm’s leadership positions on the firm’s culture and its performance. Part of the project involves the textual analysis of internal documents (e.g., emails), before and after the leadership change. To provide an example, textual analysis of these documents will be conducted to identify power relationships within the organization and study how they evolved over time.<br />
<br />
REQUIREMENTS/QUALIFICATIONS <br />
<br />
The successful candidate will work actively on novel directions in deep learning, multi-task learning, and neural networks. The candidate is expected to have:<br />
* a Ph.D. or equivalent in Computer Science, Computational Linguistics/NLP, Mathematics or related fields.<br />
* Good programming skills in Python.<br />
* Fluent English. Knowledge of other languages is more than welcome. Knowledge of Italian is NOT a requirement.<br />
* Knowledge of current neural network models, especially Word2Vec and Doc2Vec, and tools for neural networks (e.g. Tensorflow, Keras, PyTorch, etc.).<br />
* Publications in top-tier venues in the field of Computational Linguistics.<br />
* Experience in Ph.D. student supervision is a plus.<br />
* Salary: 43,310.50 euros per annum<br />
<br />
HOW TO APPLY <br />
<br />
The application must be sent to Faculty and Research Division of Bocconi University (addressing the Rector) just via email at recruiting_ricerca@unibocconi.it <br />
You can find more information about the project and call here: https://bit.ly/2t1DnAO<br />
<br />
== Postdocs: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Postdoctoral Researcher<br />
*Location: Baltimore, MD<br />
*Deadline: Applications will be accepted until positions are filled<br />
*Date Posted: June 6, 2018<br />
*Contact: clspsearch@clsp.jhu.edu<br />
*URL: https://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech, natural language processing and machine learning. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available. A single application will be considered for all open positions (except for one position as noted below). You need not indicate a specific position, but you may include a strong preference in an optional cover letter.<br />
<br />
Example topics include:<br />
* Cross-lingual Information Retrieval<br />
* Trend Detection in Social Media<br />
* Social Media and Mental Health<br />
* Analysis of Clinical Medical Text<br />
* Broadly Multilingual Learning of Morphology and Low-Resource Machine Translation<br />
* NLP and Machine Learning for Clinical Data Analysis<br />
<br />
Johns Hopkins University is a private university located in Baltimore, Maryland. The campus provides easy access to a number of affordable and vibrant neighborhoods and waterfront dining options. Hopkins is also connected to Washington DC (40 mins), Philadelphia (1.5 hours) and New York city (2.5 hours) via direct trains and buses.<br />
<br />
CLSP is one of the world’s largest academic centers focused on speech and language. CLSP is home to a dozen faculty members, half a dozen postdocs, and over 60 graduate students. It has a history of placing students in top academic and industry positions, with a large network of alumni at Google, Amazon, Microsoft Research, Bloomberg, IBM Research, Facebook, Twitter, Nuance, BBN, and numerous startups.<br />
<br />
Applicants are not required to be to US citizens or permanent residents.<br />
<br />
Questions about specific projects should be directed to the contact information associated with the project. General inquiries may be sent to clspsearch@clsp.jhu.edu.<br />
<br />
Details and application information:<br />
http://www.clsp.jhu.edu/employment-opportunities/<br />
<br />
<br />
<br />
== Research Fellow in Software Engineering with a Focus on Natural Language Processing at University of Tartu, Estonia ==<br />
* Employer: University of Tartu, Institute of Computer Science, [https://sep.cs.ut.ee/ Software Engineering group]<br />
* Title: Research Fellow <br />
* Speciality: Software engineering, machine learning, natural language processing<br />
* Location: Tartu, Estonia<br />
* Deadline: June 4, 2018<br />
* Date posted: May 21, 2018<br />
* Contact: Dietmar Pfahl, Kairit Sirts (<firstname>.<lastname>@ut.ee)<br />
<br />
'''Postdoctoral position''' <br/><br />
Applications are invited for a position of Research Fellow at the Software Engineering and Information Systems Research Group, Institute of Computer Science, University of Tartu. The institute is the leading Computer Science department in the Baltics and is one of the top-2 in Central and Eastern European universities according to the field-specific Times Higher Education Ranking 2017. The Software Engineering and Information Systems group conducts research in the fields of data-driven software engineering decision support, business process management, and secure information systems design. The group is composed of 25 members, including 12 PhD students. The group places a strong emphasis on research excellence and quality of its research publications. The institute has strong ties with the local industry and manages a portfolio of half a dozen research projects in cooperation with industry partners.<br />
<br />
The successful candidate will conduct research in the field of data-driven software engineering decision support, within a team that brings together researchers specialized in software analytics, software evolution, software quality assurance, agile development methods, data mining and natural language processing. The research fellow will be expected to contribute to ongoing research projects which aim at exploiting advanced data science methods in one or more of the following application domains:<br />
<br />
* open innovation,<br />
* energy-efficient software development,<br />
* software testing.<br />
<br />
The research to be conducted is interdisciplinary. In particular, we will be closely collaborating with the natural-language processing group to leverage their expertise on analyzing unstructured data.<br />
<br />
'''Requirements''' <br/><br />
Candidates must have a PhD in Computer Science or a related discipline. Expertise in at least one of the following topics is essential: software testing, static code analysis, software evolution/maintenance, machine learning. Experience in developing research prototypes and working in collaborative research projects is desirable. The position is not term-limited. Funding is already secured for the first two years of the appointment. The continuation of the position after the first two years will depend on further funding. Remuneration will be up to 2400 euros/month. Estonia applies a flat income tax of 20% on salaries and provides public health insurance for employees.<br />
<br />
The expected start date is 1 September 2018, but a later start date can be negotiated.<br />
<br />
The deadline for applications is 4 June 2018. The application procedure is outlined in the official advertisement at the [https://www.ut.ee/en/welcome/job-offer/research-fellow-software-engineering-0 University's website].<br />
<br />
== Postdoctoral research positions in cybersecurity, natural language processing, and experimental social psychology at SUNY Albany ==<br />
* Employer: University at Albany, Research Foundation of the State University of New York, [http://www.ils.albany.edu/ ILS Institute]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Cybersecurity, natural language processing, machine learning, experimental design<br />
* Location: Albany, New York, USA <br />
* Deadline: July 31, 2018<br />
* Date posted: May 18, 2018<br />
* Contact: Tomek Strzalkowski (tomek {at} albany.edu) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* ''The Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA) Project.'' The PANACEA Project is a joint effort of communication and computer science faculty at the University at Albany, SUNY, as well as researchers at other institutions. The project aims to design, develop, and evaluate an automated system that will protect online users against current and future forms of social engineering attacks. The system will serve as an intermediary between attackers (human, automated, hybrid, coordinated) and the potential victims they target by addressing and eliminating human vulnerabilities in current cyber defense capabilities. The objectives of the project include detection and classification of social engineering attacks as well as active defenses, including engaging and identifying of the attackers.<br />
* ''The Computational Ethnography from Metaphors and Polarized Language (COMETH) Project.'' The COMETH project is a joint effort of computer science and psychology faculty at the University at Albany. The project aims to develop and validate novel computational methodology for automatically acquiring cultural models that represent the worldviews of communities and subcultures operating within the larger society. These models will be obtained using advanced natural language processing and machine learning techniques on data from online media outlets produced by different communities. The objectives of this research include (a) capturing prevalent community attitudes (sentiment and beliefs) toward key concepts such as government, rights, economic inequality, etc.; (b) showing how these attitudes evolve over time, including in response to external influences (e.g., national or international events); and (c) explaining how this system of attitudes acts like an interpretive and defensive tool by allowing the community to reject or distort incoming information. <br />
<br />
'''Requirements for the PANACEA position''' <br/><br />
For the PANACEA project, we seek a postdoctoral researcher to join our interdisciplinary team. The candidate must have a Ph.D. in Computer Science from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. This position starts September 1, 2018.<br />
* The candidates are expected to have the following skills: in-depth knowledge of current issues and methods in cybersecurity, natural language processing, socio-behavioral computing, human-computer dialogue, statistical methods of data analysis, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with methods of conversational analysis is a plus. <br />
<br />
'''Requirements for the COMETH positions''' <br/><br />
For the COMETH project, we seek '''two''' postdoctoral researchers: one in computer science and one in psychology. The candidates must have a Ph.D. in Computer Science or Psychology from an accredited college or university that was granted within the last 3 years, and evidence of advanced scholarly research in a relevant field. These positions start December 1, 2018.<br />
<br />
* The computer science candidates are expected to have the following skills: in-depth knowledge of current issues and methods in natural language processing, data science, domain modeling, socio-behavioral computing, statistical methods, and machine learning. Familiarity with empirical method of data collection and model validation is preferred. Programming expertise is essential including substantial experience with Java, Python, and C++ programming environment, as well as with Windows, Linux and Unix platforms. Linguistic background and familiarity with sentiment analysis and metaphor extraction is a plus. <br />
* The psychology candidates are expected to have following skills: substantial experience with experimental design and advanced statistical methods in experimental social psychology, and knowledge of political psychology. Experience with open science and pre-registration of research protocols will be beneficial.<br />
<br />
'''Overall Requirements''' <br/><br />
* For all postdoctoral researchers: duties include advanced research and development under the direction of the project faculty, report preparation and coordination of work of graduate student assistants. Ability to execute substantial tasks within large projects in timely fashion is essential. Candidates must also address in their applications, their ability to work with a culturally diverse population.<br />
<br />
The postdoctoral researcher appointment review will begin immediately and will close once filled. The successful candidates will be located in the Institute for Informatics, Logics, and Security Studies at the University at Albany, SUNY. The appointment is for 40 hours a week, initially for 12 to 18 months, and potentially extendible for up to 48 months, depending on the project. Expected start dates are September 1, 2018 and December 1, 2018, pending funding approval from the Federal Government sponsor. The salary is commensurate with experience.<br />
<br />
'''How to Apply''' <br/> <br />
<br />
Interested individuals should direct inquiries and submit a cover letter, resume, and three letters of reference to: Prof. Tomek Strzalkowski, Director ILS Institute, University at Albany, tomek {at} albany.edu <br />
<br />
== Two PhD positions in deep learning for natural language understanding and summarisation at Idiap, Switzerland ==<br />
* Employer: Idiap Research Institute, [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group]<br />
* Title: Two PhD positions <br />
* Speciality: Natural Language Understanding, Summarisation, Machine Learning<br />
* Location: Martigny, Switzerland <br />
* Deadline: May 31, 2018<br />
* Date posted: April 30, 2018<br />
* Contact: James Henderson (james.henderson@idiap.ch)<br />
<br />
'''Two PhD positions''' <br />
<br />
The [http://www.idiap.ch/en Idiap Research Institute] seeks qualified candidates for two PhD student position in the field of natural language understanding, developing deep learning methods for textual entailment and opinion summarisation.<br />
<br />
The research will be conducted in the framework of the Swiss NSF funded project Learning Representations of Abstraction for Opinion Summarisation. One of the successful candidates will investigate modelling abstraction relationships between texts (textual entailment), and the other will investigate summarising large collections of opinions (opinion summarisation). Opinion summarisation must abstract away from the details of individual opinions to find consensus statements which are entailed by a significant proportion of opinions.<br />
<br />
This project will model these natural language understanding tasks through fundamental advances in representation learning and deep learning architectures. The work will start from Dr. Henderson's work on modelling abstraction in deep learning architectures, where learned vectors represent entailment rather than the usual similarity. Successes in the unsupervised learning of word vectors for entailment will be extended to deep learning architectures for the compositional semantics of texts. Methods for finding the intersection of information in vectors will be extended to clustering texts by their shared content and generating abstract summaries.<br />
<br />
The ideal PhD candidate should hold a Master degree in computer science, computational linguistics or related fields. She or he should have a background in machine learning, optimisation, or natural language processing. The applicant should also have strong programming skills. <br />
<br />
The successful PhD candidates will join the [http://www.idiap.ch/en/scientific-research/natural-language-understanding Natural Language Understanding group] at Idiap, under the supervision of Dr. James Henderson. They will also become doctoral students at [http://www.epfl.ch EPFL] conditional on parallel application to, and acceptance by, the [http://phd.epfl.ch/applicants EPFL Doctoral School]. Appointment for the PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 47,000 Swiss Francs (first year) to 50,000 Swiss Francs (last year). Starting date is to be negotiated, within 2018. All queries related to the advertised position can be sent to Dr. James Henderson (james.henderson@idiap.ch).<br />
<br />
Please apply online here:<br />
[http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710241%27%7D]<br />
<br />
'''Idiap'''<br />
<br />
Idiap is an independent, not-for-profit, research institute funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. It is located in a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative.<br />
<br />
<br />
<br />
== 2 postdoctoral research positions in text mining and natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: Postdoctoral researcher <br />
* Speciality: Text mining, natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''Postdoctoral positions''' <br/><br />
<br />
* Postdoctoral position on the topic of multilingual text mining. The goal is to build interlingual representations that allow multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. This postdoctoral position will be funded by the EU ITEA3 grant PAPUD and offers a contract for two years. The position will start as soon as possible.<br />
* Postdoctoral position on the topic of multimodal representation learning. The goal is to learn continuous representations that represent language grounded in visual perception (static images and video), assist in the design of novel machine learning architectures, and investigate suitable data structures for real-time search of the representations. This postdoctoral position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS and offers a contract for two years (with the possibility of renewal for another two years). The position will start September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*PhD in computer science or equivalent.<br />
* Motivated interest in and preferably knowledge of (as demonstrated by publications in highly recognized venues such as ACL, EMNLP, ICML, NIPS, etc.) of natural language processing and machine learning, including deep learning and learning of latent variable models. For the second postdoctoral position, interest or experience in semantic hashing is a plus.<br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== 2 PhD positions in natural language understanding at KU Leuven, Belgium ==<br />
* Employer: KU Leuven, Department of Computer Science, [https://liir.cs.kuleuven.be/ Language Intelligence and Information Retrieval lab]<br />
* Title: PhD researcher <br />
* Speciality: Natural language understanding, machine learning<br />
* Location: Leuven, Belgium <br />
* Deadline: May 21, 2018<br />
* Date posted: April 23, 2018<br />
* Contact: Sien Moens (sien.moens {at} cs.kuleuven.be) <br />
<br />
'''PhD positions''' <br/><br />
<br />
* PhD position on the topic of multimodal representation learning trained on language and visual data. The goal is to learn continuous representations of language grounded in visual data (static images and video) including the design, implementation and evaluation of novel machine learning architectures that capture textual as well as visual grammars. The learned representations will serve as commonsense knowledge in language understanding tasks. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
* PhD position on the topic of semantic parsing of natural language sentences and discourse. The goal is to learn compositional models that take into account continuous representations of objects, their attributes and likely relationships. An additional focus is on using the compositional models to efficiently parse language in real-time. This PhD position will be funded by the ERC (European Research Council) Advanced Grant CALCULUS. The position starts September 1, 2018.<br />
<br />
'''Requirements''' <br/><br />
*Master degree in computer science or equivalent.<br />
*Motivated interest in and preferably knowledge of (as demonstrated in master thesis or master course work) of natural language processing, machine learning, including deep learning and learning of latent variable models, semi-supervised machine learning, and constrained optimization. <br />
<br />
The successful candidates will have an opportunity to work on cutting-edge natural language processing, multimedia processing and machine learning research. He/she will be given the opportunity for personal development beyond research, for example by contributing to departmental teaching at the undergraduate and graduate levels. <br />
KU Leuven is an institution for research and education with international appeal. All programmes at this University are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!<br />
<br />
== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12198Employment opportunities, postdoctoral positions, summer jobs2018-03-19T07:57:25Z<p>Tristan Miller: </p>
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== Associate Research Scientist (NLP, machine learning and text mining), TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP, machine learning, text mining<br />
* Location: Darmstadt<br />
* Deadline: March 28, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an<br />
<br />
'''Associate Research Scientist'''<br />
(PostDoc- or PhD-level; for a term of three years with an extension option)<br />
<br />
This position is intended to strengthen the profile of [https://www.ukp.tu-darmstadt.de/ the lab] in a research area within natural language processing (NLP), machine learning and text mining, such as word-/sentence-/discourse-level semantics, robust textual inference, and the applications of the above in higher-level NLP, such as QA, text summarization, argument mining, etc. The lab closely cooperates with the groups in machine learning, computer vision, and interactive data analytics of the Computer Science department and many other research labs and companies. Besides, the lab conducts research projects in close cooperation with the users in the humanities and social sciences.<br />
<br />
We ask for applications from highly qualified candidates with a specialization/PhD in NLP/Text Mining, preferably with relevant research and teaching experience and strong communication skills in English and German (optional). Individual career development plans can be worked out. E.g. the successful candidate will contribute to research activities described above and – based on the previous experience and qualifications – will be given an opportunity to grow, i.e. to teach courses, co-supervise PhD students, and manage research projects. Outstanding candidates (at M.Sc.-level, without a PhD) are invited to apply and can be considered for a PhD-level position with an adjusted scope of responsibilities. The position being filled is based on the university funds.<br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG and the BMBF-funded [https://www.cedifor.de/en/cedifor/ Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR)] emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via [https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment the application form] by '''March 28, 2018'''. The position is open until filled.<br />
<br />
== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12197Employment opportunities, postdoctoral positions, summer jobs2018-03-19T07:53:58Z<p>Tristan Miller: PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning</p>
<hr />
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== PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Natural Language Processing and Machine Learning ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt]<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing and Machine Learning<br />
* Location: Darmstadt<br />
* Deadline: April 3, 2018<br />
* Date posted: March 19, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in 2015 at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling two positions for three years, starting as soon as possible, located in Darmstadt and associated with UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis in natural language processing tasks such as structured summaries of complex contents, in content selection and classification enhanced by reasoning, or a related area.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge acquisition on the Web in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, computer vision, and automated quality assessment will be developed. AIPHES will investigate a novel, complex scenario for information preparation from heterogeneous sources. It interacts closely with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.<br />
<br />
AIPHES emphasizes close contact between the students and their advisors with regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. Participating research groups at Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning (Prof. Kersting), Visual Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at Ruprecht Karls University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of the Heidelberg Institute for Theoretical Studies (HITS). AIPHES strives to publish its results at leading scientific conferences and is actively supporting its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Machine Learning, NLP, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Prior experience in scientific work is a plus. Applicants should be willing to work on lesser-resources languages, e.g. German, and, if necessary, to acquire basic German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.<br />
<br />
The research environment is excellent. The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly ranked among the top ones in respective rankings of German universities. [https://www.ukp.tu-darmstadt.de/ UKP Lab] is a highly dynamic research group committed to top-level conferences, technologies of the highest standards, cooperative work style and close interaction of team members. Its BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP, machine learning and text mining. The large-scale [http://www.argumentext.de/ argument mining project] allows searching large document collections in response to a user-defined topic: neural networks determine relevant pro and con arguments in real-time, and represent them in a concise summary.<br />
<br />
Applications should include a motivational letter that refers to one of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with information about the applicant’s scientific work, certifications of study and work experience, as well as a thesis or other publications in electronic form. Application materials must be submitted via the following form by '''April 3rd, 2018''': https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/<br />
<br />
In addition, applicants should be prepared to solve a programming and a reviewing task in the first two weeks after their application.<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12196Employment opportunities, postdoctoral positions, summer jobs2018-03-19T07:48:29Z<p>Tristan Miller: archiving 2017 positions to the 2018 page</p>
<hr />
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<br />
<br />
== Tenure track at IDSIA (Switzerland) in Natural Language Understanding and Text Mining ==<br />
* Employer: IDSIA (www.idsia.ch)<br />
* Title: Tenure track<br />
* Specialty: Natural Language Understanding and Text Mining<br />
* Location: Lugano, Switzerland <br />
* Deadline: March 31th, 2018 (start date flexible)<br />
* Date posted: March 16, 2018<br />
* Contact email: Giorgio Corani (giorgio.corani@supsi.ch)<br />
<br />
'''Project Description''' <br/><br />
The person hired on this position will evenly share her/his working time on two main activities:<br />
<br />
*Basic research, aiming at publications in highly rated journals and international conferences;<br />
*Applied research, collaborating with industrial partners in cutting-edge projects.<br />
<br />
A further cross-activity will be contributing to search for funding opportunities of both basic and applied research.<br />
<br />
The involved research area regards natural language understanding (probabilistic language modeling, keyword extraction, text summarization), text mining (text classification, word embedding, topic models) and semantic analysis of the text.<br />
<br />
'''Requirements''' <br/><br />
*The position is for a young researcher who has already obtained a PhD on a topic relevant to Natural Language Processing and/or Text Mining;<br />
*Master in informatics or other areas with strong emphasis on computation;<br />
*Excellent programming skills and deep knowledge of libraries for natural language processing;<br />
*Communication and collaboration skills.<br />
*Proficiency in written and spoken in English.<br />
<br />
<br />
'''Optional but preferential''' <br/><br />
<br />
*Strong publications record;<br />
*Capability of leading projects carried out with industrial partners on automatic analysis of documents;<br />
*Good knowledge of machine learning algorithms and tools;<br />
*Good knowledge of written and spoken Italian, or willingness to learn it in short times.<br />
<br />
'''We offer''' <br/><br />
<br />
*A tenure track position (degree of occupancy 100%) <br />
*International working environment;<br />
*Collaboration with a strong team of researchers in Machine Learning and Statistics (our publication record is available at: [http://ipg.idsia.ch]);<br />
*Salary starting from 80,000 CHF / year (about 84,000 $/year)<br />
<br />
'''Application''' <br/><br />
Applicants should submit the following documents, written in English:<br />
<br />
*curriculum vitae <br />
*list of exams and grades obtained during the Bachelor and the Master of Science;<br />
*list of three references (with e-mail addresses);<br />
*brief statement on how their research interests fit the topics above (1-2 pages);<br />
*publications list and possibly link to the thesis.<br />
<br />
Applications should be submitted through the [http://www.form-ru.app.supsi.ch/view.php?id=276008 Application website]<br />
<br />
== Postdoctoral position in Psychology at University of Pennsylvania==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Specialty: Computational Linguistics<br />
* Location: Philadelphia, Pennsylvania <br />
* Deadline: March 20th, 2018 (start date flexible)<br />
* Date posted: February 27, 2018<br />
* Contact email: Sudeep Bhatia (bhatiasu@sas.upenn.edu)<br />
<br />
'''Project Description''' <br/><br />
The researcher will study how word embeddings and related techniques can be used to model how people represent objects and events, and, in turn, predict human probability judgment, event forecasting, social judgment, risk perception, and consumer behavior. <br />
<br />
'''Requirements''' <br/><br />
Candidates should have completed (or should be about to complete) a PhD in Computer Science, Psychology , Cognitive Science, or related fields, and should be interested in applying natural language processing to address questions in Psychology, Policy, Economics, and Marketing. Applicants should have graduate-level expertise in natural language processing and machine learning. <br />
<br />
'''Additional Details''' <br/><br />
The position will be based in the Psychology department at the University of Pennsylvania, and will be supervised by Sudeep Bhatia. Lyle Ungar will serve as a second advisor. The postdoctoral researcher will also be encouraged to interact with the broader intellectual community at Penn. The appointment is expected to begin Sept 1, 2018 (start date is flexible). The term of hiring is one year, renewable for up to one additional year. The position is full time and there are no teaching or administrative responsibilities. <br />
<br />
'''How to Apply''' <br/><br />
Applications for the positions must be submitted by March 20th, 2018, to ensure full consideration. However, review of applications will continue until the position is filled. Applicants should email a curriculum vitae and contact information for two references to Sudeep Bhatia at bhatiasu@sas.upenn.edu.<br />
<br />
== Postdoctoral Research Scientist: Computational Linguistics - Rochester Institute of Technology ==<br />
* Employer: Rochester Institute of Technology<br />
* Title: Postdoctoral Research Scientist<br />
* Specialty: Postdoctoral Research Scientist: Computational Linguistics<br />
* Location: Rochester, New York, United States<br />
* Deadline: Open until filled<br />
* Date posted: February 17, 2018<br />
* Contact: Cecilia O. Alm ([mailto:coagla@rit.edu coagla@rit.edu])<br />
* [https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5289#jobDetails=1404561_5289 Job listing]<br />
<br />
We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.<br />
<br />
'''Required Minimum Qualifications:''' <br/><br />
* PhD., with training in Computational Linguistics, Linguistics, or an allied field<br />
* Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly<br />
* Publication record and plan for research and grant seeking activities<br />
* Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences<br />
<br />
'''Required Application Documents:'''<br/><br />
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement<br />
<br />
'''How To Apply:'''<br/><br />
Please apply at: [http://careers.rit.edu/staff http://careers.rit.edu/staff]. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.<br />
<br />
== Postdoctoral Research Fellow: Automated Text Analysis - University of Michigan ==<br />
<br />
* Employer: University of Michigan<br />
* Title: Research Fellow<br />
* Specialty: Postdoctoral Research Fellow: Automated Text Analysis<br />
* Location: Ann Arbor, Michigan, United States<br />
* Deadline: March 12, 2018, desired start June 2018<br />
* Date posted: February 12, 2018<br />
* [http://careers.umich.edu/job_detail/153763/postdoctoral_research_fellow_automated_text_analysis Official Job Listing - Application Page]<br />
<br />
'''How to Apply''' <br/><br />
A cover letter is required for consideration for this position and should be included as the first page of your CV. The cover letter should outline your specific interest in the position and outline skills and experience that directly relates to this position.<br />
<br />
'''Job Summary''' <br/><br />
A generously funded project (2016-2021) welcomes applicants with interest in and expertise in automated text analysis. The project, M-Write, brings together researchers from writing studies, the natural sciences, and computer programming to investigate how Writing-to-Learn pedagogies promote conceptual learning by students in large-enrollment gateway courses. Students write in response to carefully crafted assignments, participate in automated peer review, and then revise their drafts. Approximately 10,000 students have already participated in M-Write courses, which means that there is already a large corpus of student writing and peer review responses, with more being added each semester. We seek a specialist in automated text analysis to join the research team. Goals include principled corpus compilation, analysis, and development of corpus-driven algorithms to support student learning of key concepts highlighted in assignments.<br />
<br />
This position will be a 12-month Post-Doctoral Fellowship beginning in June 2018 with possibility of renewal. The salary is negotiable.<br />
<br />
'''Responsibilities'''<br />
* Retrieve and create corpora for NLP and associated linguistic analysis<br />
* Develop and test systems for identifying students who appear to lack key concepts as defined by lexical and grammatical structures, discourse analysis, and possible sentiment analysis<br />
* Design a data warehouse that will facilitate the ability to collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research leading to peer-reviewed publications, and future external funding<br />
* In collaboration with other project staff collect, manage, and archive data including student interviews, student surveys, student writing samples, and academic and demographic data for students in order to conduct research that could lead to peer-reviewed publications<br />
* Organize, synthesize, and analyze project data, and write co-authored papers with project PIs for peer-reviewed articles<br />
<br />
'''Required Qualifications''' <br/><br />
Ph.D. in computational linguistics, natural language processing, machine learning, cognitive linguistics, sentiment analysis or related area. Previous research experience in textual analysis in terms of syntax (e.g. parts of speech tagging), semantics (e.g. topic segmentation) and discourse analysis is essential. Research in statistical modeling is also required. Strong computer science skills are essential, and data warehouse design skills are highly desired. Background in the theory and research of writing-to-learn pedagogies and experience with educational technology in natural language processing are desired but not required.<br />
<br />
'''Background Screening'''<br/><br />
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.<br />
<br />
'''U-M EEO/AA Statement''' <br/><br />
The University of Michigan is an equal opportunity/affirmative action employer.<br />
<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start August 2018<br />
* Date posted: February 9, 2018<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting August 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is August 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder'''<br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
<br />
== Full-time Researchers, IBM Research - Almaden ==<br />
* Employer: [http://research.ibm.com/labs/almaden/index.shtml IBM Research - Almaden]<br />
* Title: Research Staff Member<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: San Jose, California, USA<br />
* Deadline: June 1, 2018<br />
* Date posted: January 31, 2018<br />
* Contact: Yunyao Li (yunyaoli {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for talented researchers with background in Natural Language Processing and Machine Learning to join the Natural Language Processing, Entity Resolution and Discovery Department. We are actively building the next-generation knowledge engineering platform for the creation, maintenance and consumption of "industry-specific" knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such industry-specific knowledge bases are the foundation of many emerging AI services and applications.<br />
<br />
Such a platform needs to support the entire life cycle for knowledge engineering including:<br />
* Creation, maintenance and evolution of domain schema to capture domain concepts of interest<br />
* Scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources, including text analytics, entity resolution and integration, cleansing, data transformations and machine learning <br />
* Domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* Scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* Techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* Easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* Incorporating crowd sourcing and continuous evolution of the system through learning from user interactions<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in significant academic, industrial and open source impact. <br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
The research is being conducted in close collaboration with the IBM Watson division and multiple global IBM Research labs (Australia, India, and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains). <br />
<br />
We are currently looking for talented researchers with interest in system design and implementation as well as experience in one or more areas relevant to the knowledge engineering life cycle as described above, particularly those with background in Natural Language Processing and Machine Learning. You will participate in cutting edge research, build at industrial scale, and keep connected to the larger research community by regularly publishing papers and partnering with universities. <br />
<br />
'''Required'''<br />
* Bachelor's degree or equivalent in Computer Science, related technical field or equivalent practical experience.<br />
* Programming experience in one or more of the following: Java, C, C++ and/or Python.<br />
* Experience in Natural Language Processing, Computational Linguistics, Machine Learning, Large-Scale Data Management, Data Mining or Artificial Intelligence<br />
* Contribution to research communities and/or efforts, including publishing papers at conferences such as ACL, EMNLP, NIPS, AAAI, ICML, SIGMOD, VLDB, and KDD.<br />
<br />
'''Preferred'''<br />
* PhD in Computer Science, related technical field or equivalent practical experience.<br />
* Relevant work experience, including experience working within the industry or as a researcher in a lab.<br />
* Ability to design and execute on research agenda.<br />
* Strong publication record.<br />
<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities_posted_2017&diff=12195Employment opportunities posted 20172018-03-19T07:48:19Z<p>Tristan Miller: archiving 2017 positions from the 2018 page</p>
<hr />
<div>* This is an archive of employment opportunities that were posted in 2017.<br />
<br />
== 3-year research postdoc position in computational social science at Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy<br />
*Title: Postdoc<br />
*Specialty: NLP, neural networks, computational social science<br />
*Location: Milan, Italy<br />
*Starting date: March 1, 2018<br />
*Deadline: Apply by noon January 22, 2018<br />
*Date Posted: December 29, 2017 <br />
*Contact: dip.mkt@unibocconi.it<br />
<br />
'''Project Title:''' Neural methods for text analysis in the social sciences<br />
<br />
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.<br />
The full description of the position and the application details can be found at:<br />
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An<br />
<br />
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.<br />
<br />
'''Scientific sector:''' 09/H1 Information processing systems<br />
<br />
<br />
<br />
<br />
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor<br />
*Location: Baltimore, MD<br />
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled<br />
*Date Posted: December 21, 2017 <br />
*Contact: clspsearch@clsp.jhu.edu<br />
<br />
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.<br />
<br />
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.<br />
<br />
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.<br />
<br />
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.<br />
<br />
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.<br />
<br />
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references. <br />
<br />
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.<br />
<br />
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.<br />
<br />
<br />
<br />
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==<br />
<br />
*Employer: Center for Law & Economics, ETH Zurich<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Zurich, Switzerland<br />
*Deadline: Application review begins Feb 1st 2018; open until filled<br />
*Date Posted: December 20, 2017 <br />
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])<br />
<br />
<br />
'''Description:''' Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).<br />
<br />
'''Qualifications:''' Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential. <br />
<br />
'''How to Apply:''' Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.<br />
<br />
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==<br />
<br />
*Employer: Department of Computer and Information Science, University of Pennsylvania<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Philadelphia, PA<br />
*Deadline: Open until filled<br />
*Date Posted:December 17, 2017 <br />
*Contact Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
<br />
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately. <br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics. <br />
<br />
'''Qualifications:''' The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply:''' Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.<br />
<br />
==Professor in Computational linguistics at the Linguistics Department, The Graduate Center, CUNY ==<br />
* Employer: The Graduate Center, CUNY<br />
* Rank or Title: Assistant / Associate / Full Professor: Rank Open <br />
* Specialty: Computational Linguistics (see below)<br />
* Location: New York, NY, USA<br />
* Deadline: Open until filled<br />
* Date Posted: 23-0ct-2017<br />
<br />
'''Detailed Job Description:'''<br><br />
<br />
The PhD/MA Program in Linguistics (www.gc.cuny.edu/linguistics) at the Graduate Center of<br />
the City University of New York invites applications for a full-time, tenure-track, open-rank<br />
(untenured Assistant Professor to tenured Full Professor) position to begin Fall 2018.<br />
The Program is an exciting opportunity for applicants with an independent research record in<br />
computational linguistics. Applications should demonstrate exceptionally strong computational<br />
expertise. We are looking for excellent researchers working on models of language that<br />
connect computational linguistics and theoretical approaches to human language.<br />
The successful candidate should also have knowledge of several areas of applied natural<br />
language processing to the extent that they can teach graduate level courses in NLP and mentor<br />
students outside of their specific research area. Integration of applied NLP into the candidate’s<br />
research agenda would be welcome.<br />
<br />
The successful candidate will become actively involved in teaching, developing and adapting<br />
graduate curricula, and advising MA and PhD students. He or she will also have day-to- day<br />
administrative responsibilities within the Computational Linguistics track in the Program.<br />
We offer two graduate degrees specializing in computational linguistics, a 32-credit MA and a<br />
PhD. Designed as “one-of- a-kind” computational linguistics programs in the NYC area, they<br />
cater to both students with little or no computational background, as well as to students with<br />
undergraduate or industry experience in computer science or related language technologies.<br />
Certain courses are offered to Linguistics students only, but several are cross-listed with the<br />
PhD Program in Computer Science. Accordingly, demonstrated ability to teach successfully to<br />
both demographics of students is required.<br />
<br />
The ability to work in collaboration with The Graduate Center and the City University of New<br />
York to create opportunities and employment pipelines for our graduate students would be an<br />
important asset.<br />
<br />
'''About the Graduate Center:'''<br><br />
<br />
The Graduate Center (GC) is the principal doctorate-granting institution of the City University of<br />
New York (CUNY). Offering more than thirty doctoral degrees from Anthropology to Urban<br />
Education, and fostering globally significant research in a wide variety of centers and institutes,<br />
the GC provides academic training in the humanities, sciences, and social sciences. The<br />
Graduate Center is also integral to the intellectual and cultural vitality of New York City.<br />
Through its extensive public programs, The Graduate Center hosts a wide range of events -<br />
lectures, conferences, book discussions, art exhibits, concerts, and dance and theater that enrich<br />
and inform.<br />
<br />
'''Qualifications:'''<br><br />
<br />
A PhD in Linguistics, Computational Linguistics, Computer Science (with a clear specialization in<br />
language applications), or related area<br />
Extensive research experience in computational linguistics, as demonstrated by publications in<br />
peer-reviewed journals and conference proceedings<br />
Ability to teach graduate courses and supervise MA theses and PhD dissertations<br />
<br />
'''Other Qualifications:'''<br><br />
<br />
A secondary research profile in one or more of the following fields:<br />
Language Technology, Machine Learning, Statistical Approaches to Language, Data Mining,<br />
Corpus Analysis, Speech Processing.<br />
<br />
'''How to apply'''<br><br />
Go to www.cuny.edu, click Employment>Search Job Postings, then type Keywords:<br />
Computational Linguistics.<br />
<br />
== Visiting Assistant Professor in Computational Linguistics and Language Science at RIT == <br />
* Employer: Rochester Institute of Technology<br />
* Rank or Title: Visiting Assistant Professor in Computational Linguistics and Language Science <br />
* Speciality: Computational linguistics and/or innovative technical or scientific methods in language science<br />
* Location: Rochester, NY, USA<br />
* Deadline: November 25, 2017 (Review of applications begins.)<br />
* Date Posted: November 16, 2017<br />
* Contact: Cissi Ovesdotter Alm (coagla@rit.edu) and [http://apptrkr.com/1116776 http://apptrkr.com/1116776]<br />
<br />
'''Detailed Job Description:'''<br><br />
<br />
The Department of English invites applications for a Visiting Assistant Professor position, beginning in January 2018, with specialization in computational linguistics and/or innovative technical or scientific methods in language science at Rochester Institute of Technology (RIT), with a focus on one or more areas of application. Possible areas include:<br />
<br />
* Deep learning for natural language understanding<br />
* Speech and speech technology<br />
* Multimodal and linguistic sensors<br />
* Human-computer interaction<br />
* Linguistic narrative analytics <br />
<br />
The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on initiatives in artificial intelligence and in digital humanities and social sciences. The position has the possibility of extension beyond Spring 2018. <br />
<br />
The successful applicant will be a researcher and teacher with an agenda that emphasizes innovative technical methods in linguistics, for instance in natural language processing, linguistic/multimodal sensors, speech and speech technology, and/or other computational or technical approaches applied to language data. We are seeking a scholar who engages in disciplinary and interdisciplinary teamwork, student mentoring, and has a coherent plan for grant seeking activities. The right candidate will contribute to advancing our interdisciplinary language science curriculum in a college of liberal arts at a technical university. Contributions that build students' global education experiences are additionally valued. <br />
<br />
The teaching assignment may be Introduction to Language Science, Language Technology, Introduction to NLP, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, self-designed courses, or another course depending on background. <br />
<br />
We are seeking an individual who has the ability and interest in contributing to a community committed to student-centeredness; professional development and scholarship; integrity and ethics; respect, diversity and pluralism; innovation and flexibility; and teamwork and collaboration. Select to view links to RIT's [http://www.rit.edu/academicaffairs/policiesmanual/p040 core values], [http://www.rit.edu/academicaffairs/policiesmanual/p030 honor code], and [http://www.rit.edu/academicaffairs/policiesmanual/p050 statement of diversity].<br />
<br />
'''Department Description:'''<br><br />
THE UNIVERSITY AND ROCHESTER COMMUNITY: <br><br />
RIT is a national leader in professional and career-oriented education. Talented, ambitious, and creative students of all cultures and backgrounds from all 50 states and more than 100 countries have chosen to attend RIT. Founded in 1829, Rochester Institute of Technology is a privately endowed, coeducational university with nine colleges emphasizing career education and experiential learning. With approximately 15,000 undergraduates and 2,900 graduate students, RIT is one of the largest private universities in the nation. RIT offers a rich array of degree programs in engineering, science, business, and the arts, and is home to the National Technical Institute for the Deaf. RIT has been honored by The Chronicle of Higher Education as one of the “Great Colleges to Work For” for four years. RIT is a National Science Foundation ADVANCE Institutional Transformation site. RIT is responsive to the needs of dual-career couples by our membership in the Upstate NY HERC.<br />
<br />
Rochester, situated between Lake Ontario and the Finger Lakes region, is the 51st largest metro area in the United States and the third largest city in New York State. The Greater Rochester region, which is home to nearly 1.1 million people, is rich in cultural and ethnic diversity, with a population comprised of approximately 18% African and Latin Americans and another 3% of international origin. It is also home to one of the largest deaf communities per capita in the U.S. Rochester ranks 4th for “Most Affordable City" by Forbes Magazine, and MSN selected Rochester as the “#1 Most Livable Bargain Market” (for real-estate). Kiplinger named Rochester one of the top five “Best City for Families.” <br />
<br />
'''Job Requirements:'''<br><br />
* Ph.D. with training in Computational Linguistics, Linguistics, or an allied field for language science, in hand prior to appointment date.<br />
* Advanced graduate coursework in computational linguistics, including natural language and/or spoken language processing or technical methods in linguistics.<br />
* Publication record and coherent plan for research and grant seeking activities.<br />
* Evidence of outstanding teaching.<br />
* Ability to contribute in meaningful ways to the college's continuing commitment to cultural diversity, pluralism, and individual differences. <br />
<br />
'''How to Apply:'''<br><br />
Apply online at [http://apptrkr.com/1116776 http://apptrkr.com/1116776]. Please submit your online application, curriculum vitae, cover letter addressing the listed qualifications and upload the following attachments:<br />
* A research statement<br />
* A teaching statement<br />
* Copy of transcripts of graduate coursework<br />
* A sample publication <br />
* The names, addresses, and phone numbers for three references <br />
* [http://www.rit.edu/academicaffairs/policiesmanual/p050 Statement of diversity]<br />
<br />
Questions regarding this position can be directed to the search committee chair-Dr. Cecilia Ovesdotter Alm at coagla@rit.edu.<br />
<br />
Review of applications will begin on November 25, 2017 and will continue until an acceptable candidate is found.<br />
<br />
RIT does not discriminate. RIT is an equal opportunity employer that promotes and values diversity, pluralism, and inclusion. For more information or inquiries, please visit [http://www.rit.edu/fa/humanresources/ RIT/TitleIX] or the U.S. Department of Education at [https://wdcrobcolp01.ed.gov/CFAPPS/OCR/contactus.cfm ED.Gov].<br />
<br />
<br />
== Post-doctoral positions on interpretable vector space embeddings, Cardiff University, UK ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral research associate<br />
* Specialty: Knowledge graphs, conceptual spaces, vector space embeddings, statistical learning, neural networks<br />
* Location: Cardiff, UK<br />
* Deadline: 10 December 2017<br />
* Date posted: 10 November 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk schockaerts1@cardiff.ac.uk]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of the ERC funded project FLEXILOG. The overall aims of this project are (i) to learn interpretable vector space embeddings (or conceptual spaces) from a variety of structured and unstructured information sources, and (ii) to exploit these embeddings for improving statistical and symbolic inference from imperfect data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
Specifically, the aim of these posts will be to contribute to one or more of the following:<br />
<br />
* to develop methods for statistical reasoning from sparse relational data, which exploit vector space representations to impose cognitively inspired forms of regularization (e.g. the fact that concepts tend to correspond to convex regions). <br />
* to develop methods for learning modular and interpretable vector space representations of events, which can be used to predict how events will impact the actors involved (and the entities related to them), as well as the likelihood of related future events.<br />
* to evaluate these methods in applications such as zero-shot learning, textual entailment, reading comprehension, automated knowledge base completion, and entity retrieval.<br />
<br />
Successful candidates are expected to have excellent programming skills, as well as a strong background in natural language processing, machine learning, or knowledge representation. <br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
'''More information''': <br><br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Post-doctoral position in deep learning for natural language understanding at Idiap, Switzerland ==<br />
<br />
* Employer: [http://www.idiap.ch/ Idiap Research Institute], Martigny, Switzerland<br />
* Title: PostDoc<br />
* Specialty: deep learning for natural language understanding<br />
* Location: Martigny, Switzerland<br />
* Deadline: until position filled<br />
* Date posted: November 8, 2017<br />
* Contact: [mailto:james.henderson@idiap.ch james.henderson@idiap.ch]<br />
<br />
The Idiap Research Institute seeks qualified candidates for a Postdoc position in the field of natural language understanding. The research will be conducted in the framework of EU H2020 and IARPA projects, in collaboration with international consortia.<br />
<br />
The successful candidate will work with Dr. James Henderson (http://cui.unige.ch/~hendersj/) within the Natural Language Understanding group at Idiap, and have the opportunity to collaborate with other world-class researchers in machine learning, natural language processing and speech recognition at Idiap, their project partners, and nearby EPFL. The NLU group has expertise in representation learning and deep neural network structured prediction applied to syntactic/semantic parsing, semantic entailment, machine translation, information retrieval and other NLP tasks.<br />
<br />
The research will investigate deep learning architectures for cross-lingual natural language understanding and indexing. The focus can include end-to-end integration with neural speech recognition, cross-lingual and compositional representation learning, low-resource training methods, machine translation, summarisation and cross-lingual information retrieval.<br />
<br />
The ideal candidate should hold a PhD degree in computer science or a related field. She/he will have a background in natural language processing and/or machine learning, with strong programming skills and an excellent publication record. Familiarity with deep learning toolkits will be an advantage.<br />
<br />
The Postdoc position is offered on a one-year basis with the possibility of renewal based on funding and performance, with a starting salary of 80,000 CHF/year. Exceptionally qualified candidates can also be considered for a longer-term Research Associate position. Starting date is immediate or to be negotiated. Applications will be considered until the position is filled.<br />
<br />
Please apply online here:<br />
http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710223%27%7D<br />
<br />
<br />
== Researcher in Machine Learning for NLP with a Focus on Deep Learning and Machine Translation, DFKI, German Research Center for Artificial Intelligence, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ Department of Language Technology], DFKI GmbH, Saarbrücken, Germany<br />
* Title: Researcher in Machine Learning for NLP with a Focus on Deep Learning and Machine Translation<br />
* Specialty: machine learning and deep learning for machine translation<br />
* Location: Saarbrücken<br />
* Deadline: November 30, 2017<br />
* Date posted: November 6, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de josef.van_genabith@dfki.de]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning for NLP with a focus on '''Deep Learning and Machine Translation'''. Depending on track record and experience, the position is available at the Junior/Researcher/Senior level.<br />
<br />
'''Research responsibilities include''': <br><br />
* machine learning and deep learning for machine translation<br />
* publication in top-tier conferences and journals<br />
* software development and integration<br />
<br />
'''General responsibilities include''':<br><br />
* basic research as well as industry funded applied research<br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements''': <br><br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning and deep learning as well as in MT and NLP<br />
* Strong problem solving and programming skills, independent and creative thinking<br />
* Strong team working and communication skills, as well as excellent command of written and oral English. Command of German or other languages will be helpful.<br />
<br />
Successful applicants will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Starting date, duration, salary''': <br><br />
Preferred starting dates are early Spring 2018. The position is available for a duration of three years, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application''': <br><br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references.<br />
Please send your electronic application (preferably in PDF format) and inquiries to the above address referring to job opening no. 97/17/JvG.<br />
<br />
== Independent Research Group Leader, Department of Computer Science, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Department of Computer Science], Technische Universität Darmstadt, Germany<br />
* Title: AIndependent Research Group Leader<br />
* Specialty: Natural Language Processing for the Humanities<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]<br />
<br />
Independent Research Group Leader "Natural Language Processing for the <br />
Humanities", Technische Universität Darmstadt<br />
<br />
The Department of Computer Science of Technische Universität Darmstadt <br />
seeks to fill an Independent Research Group (IRG) Leader position for <br />
the initial duration of four years. The program allows young <br />
scientists to found their own research group. It is similar in spirit <br />
to DFG's Emmy Noether Program. The focus of the Independent Research <br />
Group will be on cutting-edge Natural Language Processing research <br />
with its novel applications to support humanities research, e.g. <br />
mining scientific literature, automatic discourse analysis, or <br />
multimodal content classification to identify bias or tone <br />
computationally. The goal of the position is to strengthen the rapidly <br />
growing profile of the Department in Data Analytics at the <br />
intersection of Natural Language Processing, Computer Vision, and <br />
Machine Learning on the one side, and to further develop the connection <br />
between Computer Science and the Humanities on the other side.<br />
<br />
The IRG Leader will receive an opportunity to conduct independent <br />
research and teaching, and the funding to hire a PhD student (similar <br />
to assistant professors). Candidates must have completed their PhD in <br />
Computer Science or related area, have an outstanding publication <br />
record and demonstrate experience in working with the international <br />
research community. Ideally they have held at least one postdoc <br />
position at a university other than the one they obtained their PhD <br />
degree from. The program offers competitive personal compensation and <br />
access to resources. The IRG Leaders are employed by TU Darmstadt on <br />
its own pay scale TV-TU Darmstadt. Applicants are selected based on <br />
their credentials, references, and participation in a scientific <br />
colloquium. We expect the ability to work independently, personal <br />
commitment, team and communication abilities, as well as the <br />
willingness to cooperate in a multi-disciplinary team. We specifically <br />
invite applications of women. Among those equally qualified, <br />
handicapped applicants will receive preferential consideration. <br />
International applications are particularly encouraged.<br />
<br />
The successful candidate will be given the opportunity to join the PI <br />
team of the graduate school [https://www.aiphes.tu-darmstadt.de/ "Adaptive Preparation of Information from Heterogeneous Sources" (AIPHES)]. The project conducts innovative <br />
research in a cross-disciplinary context. To that end, methods in <br />
computational linguistics, natural language processing, machine <br />
learning, network analysis, and automated quality assessment are <br />
developed. AIPHES investigates a novel scenario for information <br />
preparation from heterogeneous sources, within the application context <br />
of multi-document summarization. There is close interaction with end <br />
users who prepare textual documents in an online editorial office, and <br />
who should therefore benefit from the results of AIPHES. In-depth <br />
knowledge in one of the above areas is required. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked <br />
among the top ones in respective rankings of German universities. Its <br />
unique [https://www.cedifor.de/en/ "Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences" (CEDIFOR)] emphasizes natural language processing, text mining, machine learning, as well as <br />
scalable infrastructures for assessment and aggregation of knowledge <br />
applied to novel research problems from the Humanities domain. <br />
<br />
Applications should be submitted to <br />
https://public.ukp.informatik.tu-darmstadt.de/irgrecruitment/ by <br />
November 24, 2017 and include a research and teaching statement along <br />
with the CV, publication list, name of three academic references, and <br />
further supporting documents. In case of questions, please contact <br />
Prof. Dr. Iryna Gurevych: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]. The position is open until filled.<br />
<br />
== PostDoc / Senior Researcher, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: PostDoc / Senior Researcher<br />
* Specialty: NLP applications to humanities, social and educational sciences; multimodal analysis and large-scale knowledge extraction<br />
* Location: Darmstadt<br />
* Deadline: November 25, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
PostDoc / Senior Researcher<br />
(for an initial term of two years with an option for an extension)<br />
<br />
to strengthen the group’s expertise in the area of Natural Language Processing with its novel applications to Humanities, Social and Educational Sciences with a focus on multimodal analysis and large-scale knowledge extraction. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP). The group has a strong research profile in computational linguistics, machine learning and text mining. Core research areas include semantic text analysis and resources with their applications in multimodal information processing, knowledge discovery, and discourse analysis. The lab closely cooperates with groups in machine learning, image analysis, and interactive data analytics of the Computer Science department and a large number of research labs worldwide. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization/PhD in Natural Language Processing or Text Mining, preferably with expertise in research and development projects and strong communication skills in English and German (optional). The successful applicant will work on research and development activities within the profile area described above and – based on the previous experience and qualification – will be given an opportunity to contribute to teaching courses, PhD student co-supervision, and project management activities.<br />
<br />
Ideally, the candidates should have demonstrable experience in NLP research, designing and implementing complex (NLP and/or ML) systems, applying Machine Learning incl. neural networks to text processing (e.g. document classification, sequence classification, clustering, etc.), information retrieval and databases, scalable data processing, and strong programming skills in Python and/or Java. <br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by November 25, 2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: interactive text analysis, natural language processing infrastructure<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Text <br />
Analysis and Natural Language Processing Infrastructure. The UKP Lab <br />
is a research group comprising over 30 team members who work on <br />
various aspects of Natural Language Processing (NLP) with a rapidly <br />
developing focus on Interactive Machine Learning, and who provide a <br />
wide range of open source software packages for interactive and <br />
automatic text analysis to research and industry communities.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Natural Language Processing or Text Mining, <br />
preferably with expertise in research and development projects and <br />
strong communication skills in English and German. The successful <br />
applicant will work on research and development activities regarding <br />
text annotation by end-users (researchers, analysts, etc.), <br />
information recommendation, information retrieval, or semantic text <br />
analysis, and to create the corresponding applications and software <br />
components in coordination with the prospective end-users. <br />
<br />
Ideally, the candidates should have demonstrable experience in <br />
designing and implementing complex (NLP and/or ML) systems (frontend <br />
and backend), in applying NLP-related Machine Learning-based methods <br />
(e.g. document classification, sequence classification, clustering, <br />
etc.), experience with information retrieval systems and databases, <br />
scalable data processing, and strong programming skills especially in <br />
Java. Experience with neural network architectures and demonstrable <br />
engagement in open source projects are strong pluses.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Data Analytics” and the Research Training Group “Adaptive <br />
Information Processing of Heterogeneous Content” (AIPHES) funded by <br />
the DFG emphasize NLP, machine learning, text mining and scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members working on common <br />
goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please submit your application via the following form by November 24, <br />
2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The <br />
position is open until filled.<br />
<br />
== KU Leuven, Belgium : Researcher in Automated Reading of Documents ==<br />
<br />
* KU Leuven, Belgium: Postdoc or junior researcher in Automated Reading of Documents <br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral or research fellow<br />
* Specialty: Machine Learning and Natural Language Processing<br />
* Location: Leuven, Belgium<br />
* Deadline: Ongoing, desired start date: as soon as possible <br />
* Date posted: November 1, 2017<br />
* Contact: [mailto:sien.moens@cs.kuleuven.be Prof. Marie-Francine Moens]<br />
<br />
'''Researcher in Automated Reading of Documents''' <br/><br />
(Department of Computer Science, KU Leuven, Belgium)<br />
<br />
The Language Intelligence & Information Retrieval lab (https://liir.cs.kuleuven.be) that is part of the Human Computer Interaction group of the Department of Computer Science of KU Leuven in Belgium has an open position for a motivated researcher interested in the latest developments in artificial intelligence for the automated reading of documents. <br />
<br />
The research is carried out in the frame of the SaaS project (Self-learning SaaS platform for simplification of data-intensive customer experiences). The goal is to design, develop and test novel machine learning models that are self-learning and that can be applied for real-time processing of unstructured or semi-structured documents. Special attention will go to deep learning models relying on character-based or word-based representations of content. <br />
<br />
We offer a research position in a research team that has an outstanding international reputation in natural language processing and understanding, multimedia mining, machine learning and information retrieval. Within the team we study both theoretical modelling and challenging applications. We investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. We have a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, user generated content mining, and web mining and search. KU Leuven is located about 25 kilometers from Brussels, the capital of Europe. For the second year in a row, KU Leuven leads the Reuters ranking as Europe’s most innovative university. <br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field.<br />
* Research experience in machine learning.<br />
<br />
'''Desired'''<br />
* Good knowledge of the English language and some knowledge of French or Dutch.<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds.<br />
* Desired start date: as soon as possible.<br />
* Competitive salary. <br />
<br />
'''How to Apply''' <br/><br />
If interested, send your CV and motivation letter to Prof. Marie-Francine Moens (sien.moens@cs.kuleuven.be). The position will be filled in as soon as possible.<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Spring/Summer 2018<br />
* Date posted: October 31, 2017<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting Spring or Summer 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is Spring 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder''' <br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
== Two Postdoctoral Positions on Interpretable Vector Space Models ==<br />
*Employer: Cardiff University<br />
*Title: Postdoctoral research associate<br />
*Speciality: Neural networks, statistical relational learning, natural language processing<br />
*Location: Cardiff, UK<br />
*Deadline: November 2 2017<br />
*Date posted: October 6, 2017<br />
*Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC). The overall aims of this project are (i) to learn interpretable vector space representations of entities and their relationships, and (ii) to exploit these vector space representations for various forms of flexible reasoning with, and learning from structured data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
The aim of these positions will be to contribute to one or more of the following topics.<br />
<br />
1) Learning structured event embeddings. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with cognitively inspired representations (e.g. based on the theory of conceptual spaces). Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. <br />
<br />
2) Combining statistical relational learning with vector space models of commonsense reasoning. Low-dimensional vector space representations can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning (SRL) can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths, enabling interpretable and robust plausible reasoning from sparse relational data.<br />
<br />
3) Geometric representations of logical theories. Most vector space models for knowledge base completion simply represent entities, attributes and relations as vectors. In many domains, however, plausible inferences rely on complex dependencies that cannot be captured by such representations. As an alternative, we will develop methods in which predicates are represented as regions, and logical formulas correspond to qualitative constraints on the spatial configurations of these regions. This model will support more complex inferences than existing approaches, will allow us to exploit existing domain knowledge when learning vector space representations, and will conversely allow us derive approximate logical theories from a learned embedding.<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Salaried 4-year PhD Position in Computational Linguistics/NLP at Stockholm University ==<br />
*Employer: Stockholm University, Sweden<br />
*Title: PhD candidate<br />
*Speciality: Computational Linguistics/Natural Language Processing<br />
*Location: Stockholm, Sweden<br />
*Deadline: October 16, 2017<br />
*Date posted: September 20, 2017<br />
*Contact: [mailto:robert@ling.su.se Robert Östling]<br />
<br />
More information and application form: http://www.su.se/english/about/working-at-su/jobs?rmlang=UK&rmpage=job&rmjob=3869<br />
<br />
The Department of Linguistics at Stockholm University is looking for a new PhD candidate in the area of computational linguistics/natural language processing. PhD candidates are regular employees of Stockholm University, with a starting salary of 25,300 SEK (2,650 EUR; 3,200 USD) per month and the same benefits and social security as other University employees. The position is fully funded for 4 years. Extension up to one year is possible if the candidate performs teaching or other duties at the department, and further extension is granted in case of parental or sick leave.<br />
<br />
The choice of thesis topic is not restricted to a particular project, but should be aligned with the research profile of the department. Possible topics include multilingual NLP methods, machine translation, or computational methods for other areas of research at the department (language acquisition, linguistic typology, phonetics, sign language).<br />
<br />
Potential applicants are encouraged to contact [mailto:robert@ling.su.se Robert Östling] to discuss possible thesis projects, or other issues related to the position.<br />
<br />
== Tenure Line Assistant Professor Position in Linguistics at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Tenure Line Assistant Professor Position in Linguistics at Northwestern University<br />
*Speciality: Meaning<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2017<br />
*Date posted: September 18, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
http://www.linguistics.northwestern.edu/about/news/faculty-search.html<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line assistant professor position with a start date of September 1, 2018. We are looking for candidates with research and teaching interests in meaning, broadly construed. We are particularly interested in candidates whose research program includes cognitive, computational, and/or social approaches. The successful candidate will join a vibrant interdisciplinary community of researchers in the science of language, including computer science, philosophy, psychology, cognitive neuroscience, and speech science.<br />
<br />
To receive fullest consideration, applications should be uploaded by December 1, 2017. Candidates must hold a Ph.D. in Linguistics, Cognitive Science, Computer Science, Psychology, or a related field by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work, teaching evaluations (if available), and the names of three references (with their contact information). References will separately receive upload instructions after you have submitted your application (letters of reference should arrive as close as December 1st as possible).<br />
<br />
The Department is strongly committed to enhancing diversity, equity and inclusion in all aspects – including, but not limited to, race/ethnicity, and gender, as well as disability, sexual orientation, and gender expression and identity. We encourage applications from candidates that share this vision.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair.<br />
<br />
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12155Employment opportunities, postdoctoral positions, summer jobs2018-01-21T22:14:30Z<p>Tristan Miller: fix links</p>
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== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL)] of the <br />
Ruprecht Karls University Heidelberg is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== 3-year research postdoc position in computational social science at Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy<br />
*Title: Postdoc<br />
*Specialty: NLP, neural networks, computational social science<br />
*Location: Milan, Italy<br />
*Starting date: March 1, 2018<br />
*Deadline: Apply by noon January 22, 2018<br />
*Date Posted: December 29, 2017 <br />
*Contact: dip.mkt@unibocconi.it<br />
<br />
'''Project Title:''' Neural methods for text analysis in the social sciences<br />
<br />
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.<br />
The full description of the position and the application details can be found at:<br />
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An<br />
<br />
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.<br />
<br />
'''Scientific sector:''' 09/H1 Information processing systems<br />
<br />
<br />
<br />
<br />
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor<br />
*Location: Baltimore, MD<br />
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled<br />
*Date Posted: December 21, 2017 <br />
*Contact: clspsearch@clsp.jhu.edu<br />
<br />
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.<br />
<br />
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.<br />
<br />
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.<br />
<br />
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.<br />
<br />
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.<br />
<br />
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references. <br />
<br />
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.<br />
<br />
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.<br />
<br />
<br />
<br />
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==<br />
<br />
*Employer: Center for Law & Economics, ETH Zurich<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Zurich, Switzerland<br />
*Deadline: Application review begins Feb 1st 2018; open until filled<br />
*Date Posted: December 20, 2017 <br />
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])<br />
<br />
<br />
'''Description:''' Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).<br />
<br />
'''Qualifications:''' Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential. <br />
<br />
'''How to Apply:''' Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.<br />
<br />
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==<br />
<br />
*Employer: Department of Computer and Information Science, University of Pennsylvania<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Philadelphia, PA<br />
*Deadline: Open until filled<br />
*Date Posted:December 17, 2017 <br />
*Contact Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
<br />
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately. <br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics. <br />
<br />
'''Qualifications:''' The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply:''' Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12154Employment opportunities, postdoctoral positions, summer jobs2018-01-21T22:13:36Z<p>Tristan Miller: PhD-level Researchers, AIPHES, Darmstadt/Heidelberg</p>
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* Archived postings:<br />
** [[Employment opportunities posted 2017|2017]] - [[Employment opportunities posted 2016|2016]] - [[Employment opportunities posted 2015|2015]] - [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]<br />
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== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt or Heidelberg<br />
* Deadline: February 11, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
PhD positions in DFG Graduate School AIPHES: Natural Language <br />
Processing and Computational Linguistics<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ “Adaptive Information Preparation from <br />
Heterogeneous Sources” (AIPHES)], which has been established in <br />
2015 at Technische Universität Darmstadt and at Ruprecht Karls <br />
University Heidelberg is filling several positions for three years, <br />
starting as soon as possible. Positions remain open until filled.<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
opinion and sentiment - extrapropositional aspects of discourse, in <br />
natural language processing tasks such as structured summaries of <br />
complex contents, in content selection and classification enhanced by <br />
reasoning, or a related area. The group will be located in Darmstadt <br />
and Heidelberg. The funding follows the guidelines of the DFG, and the <br />
positions are paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at Technische Universität Darmstadt are <br />
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS).<br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors with regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite <br />
applications of women. Among those equally qualified, handicapped <br />
applicants will receive preferential consideration. International <br />
applications are particularly encouraged.<br />
<br />
The [https://www.informatik.tu-darmstadt.de/ Department of Computer Science of TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. [http://www.cl.uni-heidelberg.de/ The Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of AIPHES, a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications <br />
in <br />
electronic form. Application materials must be submitted via the <br />
following form by February 11th, 2018:<br />
<br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ <br />
<br />
In addition, applicants should be prepared to solve a programming and <br />
a reviewing task in the first two weeks after their application.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== 3-year research postdoc position in computational social science at Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy<br />
*Title: Postdoc<br />
*Specialty: NLP, neural networks, computational social science<br />
*Location: Milan, Italy<br />
*Starting date: March 1, 2018<br />
*Deadline: Apply by noon January 22, 2018<br />
*Date Posted: December 29, 2017 <br />
*Contact: dip.mkt@unibocconi.it<br />
<br />
'''Project Title:''' Neural methods for text analysis in the social sciences<br />
<br />
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.<br />
The full description of the position and the application details can be found at:<br />
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An<br />
<br />
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.<br />
<br />
'''Scientific sector:''' 09/H1 Information processing systems<br />
<br />
<br />
<br />
<br />
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor<br />
*Location: Baltimore, MD<br />
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled<br />
*Date Posted: December 21, 2017 <br />
*Contact: clspsearch@clsp.jhu.edu<br />
<br />
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.<br />
<br />
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.<br />
<br />
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.<br />
<br />
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.<br />
<br />
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.<br />
<br />
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references. <br />
<br />
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.<br />
<br />
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.<br />
<br />
<br />
<br />
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==<br />
<br />
*Employer: Center for Law & Economics, ETH Zurich<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Zurich, Switzerland<br />
*Deadline: Application review begins Feb 1st 2018; open until filled<br />
*Date Posted: December 20, 2017 <br />
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])<br />
<br />
<br />
'''Description:''' Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).<br />
<br />
'''Qualifications:''' Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential. <br />
<br />
'''How to Apply:''' Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.<br />
<br />
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==<br />
<br />
*Employer: Department of Computer and Information Science, University of Pennsylvania<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Philadelphia, PA<br />
*Deadline: Open until filled<br />
*Date Posted:December 17, 2017 <br />
*Contact Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
<br />
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately. <br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics. <br />
<br />
'''Qualifications:''' The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply:''' Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12153Employment opportunities, postdoctoral positions, summer jobs2018-01-21T22:08:13Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
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<!-- PLEASE DO NOT EDIT THIS HEADER --><br />
* '''[[Instructions for Posting Job Ads]]'''<br />
* See also the [http://linguistlist.org/jobs Linguist Job List].<br />
* Archived postings:<br />
** [[Employment opportunities posted 2017|2017]] - [[Employment opportunities posted 2016|2016]] - [[Employment opportunities posted 2015|2015]] - [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]<br />
<!-- PLEASE DO NOT EDIT THIS HEADER --><br />
<!-- PLEASE BE CAREFUL NOT TO DAMAGE ANOTHER PERSON'S AD --><br />
<!-- USE "SHOW PREVIEW" TO VERIFY YOUR EDITS --><br />
<!-- INSERT YOUR JOB AD IMMEDIATELY BELOW THIS HEADER --><br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive text analysis<br />
* Location: Darmstadt<br />
* Deadline: February 16, 2018<br />
* Date posted: January 21, 2018<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
Associate Research Scientist<br />
(PostDoc- or PhD-level; for an initial term of two years)<br />
<br />
in the areas of Interactive Text Analysis, the UKP Lab is looking for <br />
a researcher with a background in Natural Language Processing and <br />
Software Development to work on the project [https://www.ukp.tu-darmstadt.de/research/current-projects/inception/ INCEpTION] funded by <br />
the German Research Foundation (DFG). The project is developing a <br />
comprehensive interactive text analysis platform to improve efficiency <br />
and to enable new ways of exploring, annotating and analyzing <br />
large-scale text corpora through the use of assistive features based <br />
on machine-learning. <br />
<br />
We ask for applications from candidates from Computer Science with a <br />
specialization in Natural Language Processing, Text Mining, or Machine <br />
Learning, preferably with expertise in research and development <br />
projects, and strong communication skills. The successful applicant <br />
will work on research and development activities regarding text <br />
annotation by end-users (researchers, analysts, etc.), information <br />
recommendation, and create the corresponding text analysis platform. <br />
Ideally, the candidates should have demonstrable experience in <br />
designing complex (NLP and/or ML) systems (frontend and backend), in <br />
applying NLP-related Machine Learning-based methods, and strong <br />
programming skills especially in Java. Experience with neural network <br />
architectures and demonstrable engagement in open source projects are <br />
strong pluses.<br />
<br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), with a <br />
rapidly developing focus on Interactive Machine Learning and who <br />
provide a range of high-quality open source software packages for <br />
interactive and automatic text analysis to research and industry <br />
communities.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
work environment. The Department of Computer Science of TU Darmstadt <br />
is regularly ranked among the top ones in respective rankings of <br />
German universities. Its Research Training Group “Adaptive Information <br />
Processing of Heterogeneous Content” (AIPHES) funded by the DFG <br />
emphasizes NLP, machine learning, text mining, as well as scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 16.2.2018. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== 3-year research postdoc position in computational social science at Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy<br />
*Title: Postdoc<br />
*Specialty: NLP, neural networks, computational social science<br />
*Location: Milan, Italy<br />
*Starting date: March 1, 2018<br />
*Deadline: Apply by noon January 22, 2018<br />
*Date Posted: December 29, 2017 <br />
*Contact: dip.mkt@unibocconi.it<br />
<br />
'''Project Title:''' Neural methods for text analysis in the social sciences<br />
<br />
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.<br />
The full description of the position and the application details can be found at:<br />
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An<br />
<br />
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.<br />
<br />
'''Scientific sector:''' 09/H1 Information processing systems<br />
<br />
<br />
<br />
<br />
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor<br />
*Location: Baltimore, MD<br />
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled<br />
*Date Posted: December 21, 2017 <br />
*Contact: clspsearch@clsp.jhu.edu<br />
<br />
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.<br />
<br />
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.<br />
<br />
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.<br />
<br />
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.<br />
<br />
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.<br />
<br />
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references. <br />
<br />
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.<br />
<br />
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.<br />
<br />
<br />
<br />
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==<br />
<br />
*Employer: Center for Law & Economics, ETH Zurich<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Zurich, Switzerland<br />
*Deadline: Application review begins Feb 1st 2018; open until filled<br />
*Date Posted: December 20, 2017 <br />
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])<br />
<br />
<br />
'''Description:''' Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).<br />
<br />
'''Qualifications:''' Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential. <br />
<br />
'''How to Apply:''' Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.<br />
<br />
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==<br />
<br />
*Employer: Department of Computer and Information Science, University of Pennsylvania<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Philadelphia, PA<br />
*Deadline: Open until filled<br />
*Date Posted:December 17, 2017 <br />
*Contact Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
<br />
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately. <br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics. <br />
<br />
'''Qualifications:''' The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply:''' Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12152Employment opportunities, postdoctoral positions, summer jobs2018-01-21T22:00:58Z<p>Tristan Miller: Archive (presumably) closed postings from 2017</p>
<hr />
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* Archived postings:<br />
** [[Employment opportunities posted 2017|2017]] - [[Employment opportunities posted 2016|2016]] - [[Employment opportunities posted 2015|2015]] - [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]<br />
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== 3-year research postdoc position in computational social science at Bocconi University, Milan ==<br />
<br />
*Employer: Bocconi University, marketing department, supervisor Dirk Hovy<br />
*Title: Postdoc<br />
*Specialty: NLP, neural networks, computational social science<br />
*Location: Milan, Italy<br />
*Starting date: March 1, 2018<br />
*Deadline: Apply by noon January 22, 2018<br />
*Date Posted: December 29, 2017 <br />
*Contact: dip.mkt@unibocconi.it<br />
<br />
'''Project Title:''' Neural methods for text analysis in the social sciences<br />
<br />
'''Project Description:''' Text is a common medium in all social sciences, offering insights into human behavior. However, text is complex and encodes many different aspects at the same time. In order to analyze text for social science projects, we need to develop the right tools, based on natural language processing. These tools needs to scale to large amounts of text, allow for exploration and predictive modeling, and allow a multitude of analyses (classification, regression, clustering, etc). Neural-network approaches to NLP have lately demonstrated all of these properties, but have rarely been applied to social science problems. The goal of this project is to establish a baseline in tools and techniques that can be widely applied, and that can form the basis of future research and training.<br />
The full description of the position and the application details can be found at:<br />
https://www.unibocconi.eu/wps/wcm/connect/d61571c4-b0cf-4aad-a25c-b963801595bf/Call-ADR-09H1-MKT.pdf?MOD=AJPERES&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An&CVID=m1g59An<br />
<br />
'''Responsibilities:''' The candidate would work predominantly on research, i.e., the implementation and testing of model architectures, data mining and preparation, and dissemination of results. Teaching opportunities (for additional salary) are available.<br />
<br />
'''Scientific sector:''' 09/H1 Information processing systems<br />
<br />
<br />
<br />
<br />
== Teaching Faculty in Human Language Technology: Johns Hopkins University ==<br />
<br />
*Employer: Johns Hopkins University<br />
*Title: Senior Lecturer, Associate Teaching Professor or Teaching Professor<br />
*Location: Baltimore, MD<br />
*Deadline: Apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled<br />
*Date Posted: December 21, 2017 <br />
*Contact: clspsearch@clsp.jhu.edu<br />
<br />
The Center for Language and Speech Processing (CLSP) at Johns Hopkins University seeks outstanding candidates for a fulltime teaching position. The search is open to all ranks, including Senior Lecturer, Associate Teaching Professor and Teaching Professor.<br />
<br />
This position will be central to CLSP’s new Certificate in Human Language Technology, part of the master’s degree programs in Computer Science (CS) and the Electrical and Computer Engineering (ECE). The successful candidate will be involved in new course development, graduate teaching, graduate academic advising, supervising master's thesis projects, and managing various aspects of the Certificate program. Although this is primarily a teaching position, there is also potential for research effort.<br />
<br />
Successful candidates will join the faculty of CLSP, one of the largest and most visible academic organizations in speech processing and NLP. For more than two decades, CLSP has advanced the state of the art in research, hosted international research teams (the annual JSALT workshops), and produced hundreds of PhD alumni. Our graduates are found throughout most major information processing companies and in government related research organizations.<br />
<br />
The primary appointment will be in the academic department most appropriate for the candidate within the Whiting School of Engineering, such as Electrical and Computer Engineering, Computer Science or another appropriate department. Applicants for this position must have a Ph.D. in Computer Science, Electrical and Computer Engineering or a closely related field, commitment to teaching, and excellent communication skills. Familiarity with some aspect of Human Language Technology or machine learning is strongly preferred. The university has instituted a nontenure track career path for fulltime teaching faculty culminating in the rank of Teaching Professor.<br />
<br />
Johns Hopkins is a private university known for its commitment to academic excellence and research. CLSP, as well as the CS and ECE departments, are part of the Whiting School of Engineering. We are located in Baltimore, MD in close proximity to Washington, DC and Philadelphia, PA. See the center webpage https://www.clsp.jhu.edu/ for additional information.<br />
<br />
Applicants should apply online at http://apply.interfolio.com/47959. Salary and rank will be commensurate with qualifications and experience. Applicants should submit a curriculum vitae, a teaching statement and complete contact information for at least three references. <br />
<br />
Applicants should apply by January 31, 2018 for full consideration, but applications will be accepted until positions are filled. Questions should be directed to clspsearch@clsp.jhu.edu.<br />
<br />
Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.<br />
<br />
<br />
<br />
== Post-Doctoral Position: Law, Economics, & Data Science, ETH Zurich ==<br />
<br />
*Employer: Center for Law & Economics, ETH Zurich<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Zurich, Switzerland<br />
*Deadline: Application review begins Feb 1st 2018; open until filled<br />
*Date Posted: December 20, 2017 <br />
*Contact: Elliott Ash ([mailto:e@elliottash.com e@elliottash.com])<br />
<br />
<br />
'''Description:''' Applications are invited for postdoctoral research position in a new interdisciplinary research group at Center for Law & Economics, ETH Zurich. The research group in Law, Economics, and Data Science focuses on representing legal and political language as statistical data using tools from natural language processing, and then recovering causal relations between language and outcomes in society and the economy. The postdoc will be involved in all aspects of the research, including project planning, research design, data analysis, presentation of findings at conferences, and preparation of manuscripts for submission to leading peer-reviewed journals. The postdoc will have the opportunity to co-author papers with lab colleagues, work with an array of affiliated faculty from ETH and University of Zurich, and develop independent projects related to these research areas. Organizational and teaching duties are limited to a few hours per week. Our offices are located in downtown Zurich, and the working language is English. The appointment will be for at least one year and up to three years (contingent on satisfactory performance), with flexible starting date beginning July 2018. Salaries are internationally competitive, paid according to ETH standards (https://www.ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-conditions/employment-and-salary.html).<br />
<br />
'''Qualifications:''' Applicants should have a PhD in computer science, computational linguistics, machine learning, or a related field. Applicants should have graduate-level expertise in natural language processing and machine learning. Excellent English writing skills are essential. <br />
<br />
'''How to Apply:''' Online application available at https://apply.refline.ch/845721/5895/index.html?cid=1&lang=en. Application review will begin on February 1, 2018 and continue until the position is filled.<br />
<br />
== Post-Doctoral Researcher in Computational Linguistics, University of Pennsylvania ==<br />
<br />
*Employer: Department of Computer and Information Science, University of Pennsylvania<br />
*Title: Post-Doctoral Research Fellow<br />
*Location: Philadelphia, PA<br />
*Deadline: Open until filled<br />
*Date Posted:December 17, 2017 <br />
*Contact Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
<br />
'''Description:''' Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 18 months, starting immediately. <br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years. Our project is also inspired by the current understanding of how children acquire their native language, in an unsupervised setting and with relatively small amount of data. We intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics. <br />
<br />
'''Qualifications:''' The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply:''' Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided below.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities_posted_2017&diff=12151Employment opportunities posted 20172018-01-21T21:59:46Z<p>Tristan Miller: Archiving old job posts</p>
<hr />
<div>* This is an archive of employment opportunities that were posted in 2017.<br />
<br />
==Professor in Computational linguistics at the Linguistics Department, The Graduate Center, CUNY ==<br />
* Employer: The Graduate Center, CUNY<br />
* Rank or Title: Assistant / Associate / Full Professor: Rank Open <br />
* Specialty: Computational Linguistics (see below)<br />
* Location: New York, NY, USA<br />
* Deadline: Open until filled<br />
* Date Posted: 23-0ct-2017<br />
<br />
'''Detailed Job Description:'''<br><br />
<br />
The PhD/MA Program in Linguistics (www.gc.cuny.edu/linguistics) at the Graduate Center of<br />
the City University of New York invites applications for a full-time, tenure-track, open-rank<br />
(untenured Assistant Professor to tenured Full Professor) position to begin Fall 2018.<br />
The Program is an exciting opportunity for applicants with an independent research record in<br />
computational linguistics. Applications should demonstrate exceptionally strong computational<br />
expertise. We are looking for excellent researchers working on models of language that<br />
connect computational linguistics and theoretical approaches to human language.<br />
The successful candidate should also have knowledge of several areas of applied natural<br />
language processing to the extent that they can teach graduate level courses in NLP and mentor<br />
students outside of their specific research area. Integration of applied NLP into the candidate’s<br />
research agenda would be welcome.<br />
<br />
The successful candidate will become actively involved in teaching, developing and adapting<br />
graduate curricula, and advising MA and PhD students. He or she will also have day-to- day<br />
administrative responsibilities within the Computational Linguistics track in the Program.<br />
We offer two graduate degrees specializing in computational linguistics, a 32-credit MA and a<br />
PhD. Designed as “one-of- a-kind” computational linguistics programs in the NYC area, they<br />
cater to both students with little or no computational background, as well as to students with<br />
undergraduate or industry experience in computer science or related language technologies.<br />
Certain courses are offered to Linguistics students only, but several are cross-listed with the<br />
PhD Program in Computer Science. Accordingly, demonstrated ability to teach successfully to<br />
both demographics of students is required.<br />
<br />
The ability to work in collaboration with The Graduate Center and the City University of New<br />
York to create opportunities and employment pipelines for our graduate students would be an<br />
important asset.<br />
<br />
'''About the Graduate Center:'''<br><br />
<br />
The Graduate Center (GC) is the principal doctorate-granting institution of the City University of<br />
New York (CUNY). Offering more than thirty doctoral degrees from Anthropology to Urban<br />
Education, and fostering globally significant research in a wide variety of centers and institutes,<br />
the GC provides academic training in the humanities, sciences, and social sciences. The<br />
Graduate Center is also integral to the intellectual and cultural vitality of New York City.<br />
Through its extensive public programs, The Graduate Center hosts a wide range of events -<br />
lectures, conferences, book discussions, art exhibits, concerts, and dance and theater that enrich<br />
and inform.<br />
<br />
'''Qualifications:'''<br><br />
<br />
A PhD in Linguistics, Computational Linguistics, Computer Science (with a clear specialization in<br />
language applications), or related area<br />
Extensive research experience in computational linguistics, as demonstrated by publications in<br />
peer-reviewed journals and conference proceedings<br />
Ability to teach graduate courses and supervise MA theses and PhD dissertations<br />
<br />
'''Other Qualifications:'''<br><br />
<br />
A secondary research profile in one or more of the following fields:<br />
Language Technology, Machine Learning, Statistical Approaches to Language, Data Mining,<br />
Corpus Analysis, Speech Processing.<br />
<br />
'''How to apply'''<br><br />
Go to www.cuny.edu, click Employment>Search Job Postings, then type Keywords:<br />
Computational Linguistics.<br />
<br />
== Visiting Assistant Professor in Computational Linguistics and Language Science at RIT == <br />
* Employer: Rochester Institute of Technology<br />
* Rank or Title: Visiting Assistant Professor in Computational Linguistics and Language Science <br />
* Speciality: Computational linguistics and/or innovative technical or scientific methods in language science<br />
* Location: Rochester, NY, USA<br />
* Deadline: November 25, 2017 (Review of applications begins.)<br />
* Date Posted: November 16, 2017<br />
* Contact: Cissi Ovesdotter Alm (coagla@rit.edu) and [http://apptrkr.com/1116776 http://apptrkr.com/1116776]<br />
<br />
'''Detailed Job Description:'''<br><br />
<br />
The Department of English invites applications for a Visiting Assistant Professor position, beginning in January 2018, with specialization in computational linguistics and/or innovative technical or scientific methods in language science at Rochester Institute of Technology (RIT), with a focus on one or more areas of application. Possible areas include:<br />
<br />
* Deep learning for natural language understanding<br />
* Speech and speech technology<br />
* Multimodal and linguistic sensors<br />
* Human-computer interaction<br />
* Linguistic narrative analytics <br />
<br />
The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on initiatives in artificial intelligence and in digital humanities and social sciences. The position has the possibility of extension beyond Spring 2018. <br />
<br />
The successful applicant will be a researcher and teacher with an agenda that emphasizes innovative technical methods in linguistics, for instance in natural language processing, linguistic/multimodal sensors, speech and speech technology, and/or other computational or technical approaches applied to language data. We are seeking a scholar who engages in disciplinary and interdisciplinary teamwork, student mentoring, and has a coherent plan for grant seeking activities. The right candidate will contribute to advancing our interdisciplinary language science curriculum in a college of liberal arts at a technical university. Contributions that build students' global education experiences are additionally valued. <br />
<br />
The teaching assignment may be Introduction to Language Science, Language Technology, Introduction to NLP, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, self-designed courses, or another course depending on background. <br />
<br />
We are seeking an individual who has the ability and interest in contributing to a community committed to student-centeredness; professional development and scholarship; integrity and ethics; respect, diversity and pluralism; innovation and flexibility; and teamwork and collaboration. Select to view links to RIT's [http://www.rit.edu/academicaffairs/policiesmanual/p040 core values], [http://www.rit.edu/academicaffairs/policiesmanual/p030 honor code], and [http://www.rit.edu/academicaffairs/policiesmanual/p050 statement of diversity].<br />
<br />
'''Department Description:'''<br><br />
THE UNIVERSITY AND ROCHESTER COMMUNITY: <br><br />
RIT is a national leader in professional and career-oriented education. Talented, ambitious, and creative students of all cultures and backgrounds from all 50 states and more than 100 countries have chosen to attend RIT. Founded in 1829, Rochester Institute of Technology is a privately endowed, coeducational university with nine colleges emphasizing career education and experiential learning. With approximately 15,000 undergraduates and 2,900 graduate students, RIT is one of the largest private universities in the nation. RIT offers a rich array of degree programs in engineering, science, business, and the arts, and is home to the National Technical Institute for the Deaf. RIT has been honored by The Chronicle of Higher Education as one of the “Great Colleges to Work For” for four years. RIT is a National Science Foundation ADVANCE Institutional Transformation site. RIT is responsive to the needs of dual-career couples by our membership in the Upstate NY HERC.<br />
<br />
Rochester, situated between Lake Ontario and the Finger Lakes region, is the 51st largest metro area in the United States and the third largest city in New York State. The Greater Rochester region, which is home to nearly 1.1 million people, is rich in cultural and ethnic diversity, with a population comprised of approximately 18% African and Latin Americans and another 3% of international origin. It is also home to one of the largest deaf communities per capita in the U.S. Rochester ranks 4th for “Most Affordable City" by Forbes Magazine, and MSN selected Rochester as the “#1 Most Livable Bargain Market” (for real-estate). Kiplinger named Rochester one of the top five “Best City for Families.” <br />
<br />
'''Job Requirements:'''<br><br />
* Ph.D. with training in Computational Linguistics, Linguistics, or an allied field for language science, in hand prior to appointment date.<br />
* Advanced graduate coursework in computational linguistics, including natural language and/or spoken language processing or technical methods in linguistics.<br />
* Publication record and coherent plan for research and grant seeking activities.<br />
* Evidence of outstanding teaching.<br />
* Ability to contribute in meaningful ways to the college's continuing commitment to cultural diversity, pluralism, and individual differences. <br />
<br />
'''How to Apply:'''<br><br />
Apply online at [http://apptrkr.com/1116776 http://apptrkr.com/1116776]. Please submit your online application, curriculum vitae, cover letter addressing the listed qualifications and upload the following attachments:<br />
* A research statement<br />
* A teaching statement<br />
* Copy of transcripts of graduate coursework<br />
* A sample publication <br />
* The names, addresses, and phone numbers for three references <br />
* [http://www.rit.edu/academicaffairs/policiesmanual/p050 Statement of diversity]<br />
<br />
Questions regarding this position can be directed to the search committee chair-Dr. Cecilia Ovesdotter Alm at coagla@rit.edu.<br />
<br />
Review of applications will begin on November 25, 2017 and will continue until an acceptable candidate is found.<br />
<br />
RIT does not discriminate. RIT is an equal opportunity employer that promotes and values diversity, pluralism, and inclusion. For more information or inquiries, please visit [http://www.rit.edu/fa/humanresources/ RIT/TitleIX] or the U.S. Department of Education at [https://wdcrobcolp01.ed.gov/CFAPPS/OCR/contactus.cfm ED.Gov].<br />
<br />
<br />
== Post-doctoral positions on interpretable vector space embeddings, Cardiff University, UK ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral research associate<br />
* Specialty: Knowledge graphs, conceptual spaces, vector space embeddings, statistical learning, neural networks<br />
* Location: Cardiff, UK<br />
* Deadline: 10 December 2017<br />
* Date posted: 10 November 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk schockaerts1@cardiff.ac.uk]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of the ERC funded project FLEXILOG. The overall aims of this project are (i) to learn interpretable vector space embeddings (or conceptual spaces) from a variety of structured and unstructured information sources, and (ii) to exploit these embeddings for improving statistical and symbolic inference from imperfect data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
Specifically, the aim of these posts will be to contribute to one or more of the following:<br />
<br />
* to develop methods for statistical reasoning from sparse relational data, which exploit vector space representations to impose cognitively inspired forms of regularization (e.g. the fact that concepts tend to correspond to convex regions). <br />
* to develop methods for learning modular and interpretable vector space representations of events, which can be used to predict how events will impact the actors involved (and the entities related to them), as well as the likelihood of related future events.<br />
* to evaluate these methods in applications such as zero-shot learning, textual entailment, reading comprehension, automated knowledge base completion, and entity retrieval.<br />
<br />
Successful candidates are expected to have excellent programming skills, as well as a strong background in natural language processing, machine learning, or knowledge representation. <br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
'''More information''': <br><br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Post-doctoral position in deep learning for natural language understanding at Idiap, Switzerland ==<br />
<br />
* Employer: [http://www.idiap.ch/ Idiap Research Institute], Martigny, Switzerland<br />
* Title: PostDoc<br />
* Specialty: deep learning for natural language understanding<br />
* Location: Martigny, Switzerland<br />
* Deadline: until position filled<br />
* Date posted: November 8, 2017<br />
* Contact: [mailto:james.henderson@idiap.ch james.henderson@idiap.ch]<br />
<br />
The Idiap Research Institute seeks qualified candidates for a Postdoc position in the field of natural language understanding. The research will be conducted in the framework of EU H2020 and IARPA projects, in collaboration with international consortia.<br />
<br />
The successful candidate will work with Dr. James Henderson (http://cui.unige.ch/~hendersj/) within the Natural Language Understanding group at Idiap, and have the opportunity to collaborate with other world-class researchers in machine learning, natural language processing and speech recognition at Idiap, their project partners, and nearby EPFL. The NLU group has expertise in representation learning and deep neural network structured prediction applied to syntactic/semantic parsing, semantic entailment, machine translation, information retrieval and other NLP tasks.<br />
<br />
The research will investigate deep learning architectures for cross-lingual natural language understanding and indexing. The focus can include end-to-end integration with neural speech recognition, cross-lingual and compositional representation learning, low-resource training methods, machine translation, summarisation and cross-lingual information retrieval.<br />
<br />
The ideal candidate should hold a PhD degree in computer science or a related field. She/he will have a background in natural language processing and/or machine learning, with strong programming skills and an excellent publication record. Familiarity with deep learning toolkits will be an advantage.<br />
<br />
The Postdoc position is offered on a one-year basis with the possibility of renewal based on funding and performance, with a starting salary of 80,000 CHF/year. Exceptionally qualified candidates can also be considered for a longer-term Research Associate position. Starting date is immediate or to be negotiated. Applications will be considered until the position is filled.<br />
<br />
Please apply online here:<br />
http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710223%27%7D<br />
<br />
<br />
== Researcher in Machine Learning for NLP with a Focus on Deep Learning and Machine Translation, DFKI, German Research Center for Artificial Intelligence, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ Department of Language Technology], DFKI GmbH, Saarbrücken, Germany<br />
* Title: Researcher in Machine Learning for NLP with a Focus on Deep Learning and Machine Translation<br />
* Specialty: machine learning and deep learning for machine translation<br />
* Location: Saarbrücken<br />
* Deadline: November 30, 2017<br />
* Date posted: November 6, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de josef.van_genabith@dfki.de]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning for NLP with a focus on '''Deep Learning and Machine Translation'''. Depending on track record and experience, the position is available at the Junior/Researcher/Senior level.<br />
<br />
'''Research responsibilities include''': <br><br />
* machine learning and deep learning for machine translation<br />
* publication in top-tier conferences and journals<br />
* software development and integration<br />
<br />
'''General responsibilities include''':<br><br />
* basic research as well as industry funded applied research<br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements''': <br><br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning and deep learning as well as in MT and NLP<br />
* Strong problem solving and programming skills, independent and creative thinking<br />
* Strong team working and communication skills, as well as excellent command of written and oral English. Command of German or other languages will be helpful.<br />
<br />
Successful applicants will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Starting date, duration, salary''': <br><br />
Preferred starting dates are early Spring 2018. The position is available for a duration of three years, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application''': <br><br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references.<br />
Please send your electronic application (preferably in PDF format) and inquiries to the above address referring to job opening no. 97/17/JvG.<br />
<br />
== Independent Research Group Leader, Department of Computer Science, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Department of Computer Science], Technische Universität Darmstadt, Germany<br />
* Title: AIndependent Research Group Leader<br />
* Specialty: Natural Language Processing for the Humanities<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]<br />
<br />
Independent Research Group Leader "Natural Language Processing for the <br />
Humanities", Technische Universität Darmstadt<br />
<br />
The Department of Computer Science of Technische Universität Darmstadt <br />
seeks to fill an Independent Research Group (IRG) Leader position for <br />
the initial duration of four years. The program allows young <br />
scientists to found their own research group. It is similar in spirit <br />
to DFG's Emmy Noether Program. The focus of the Independent Research <br />
Group will be on cutting-edge Natural Language Processing research <br />
with its novel applications to support humanities research, e.g. <br />
mining scientific literature, automatic discourse analysis, or <br />
multimodal content classification to identify bias or tone <br />
computationally. The goal of the position is to strengthen the rapidly <br />
growing profile of the Department in Data Analytics at the <br />
intersection of Natural Language Processing, Computer Vision, and <br />
Machine Learning on the one side, and to further develop the connection <br />
between Computer Science and the Humanities on the other side.<br />
<br />
The IRG Leader will receive an opportunity to conduct independent <br />
research and teaching, and the funding to hire a PhD student (similar <br />
to assistant professors). Candidates must have completed their PhD in <br />
Computer Science or related area, have an outstanding publication <br />
record and demonstrate experience in working with the international <br />
research community. Ideally they have held at least one postdoc <br />
position at a university other than the one they obtained their PhD <br />
degree from. The program offers competitive personal compensation and <br />
access to resources. The IRG Leaders are employed by TU Darmstadt on <br />
its own pay scale TV-TU Darmstadt. Applicants are selected based on <br />
their credentials, references, and participation in a scientific <br />
colloquium. We expect the ability to work independently, personal <br />
commitment, team and communication abilities, as well as the <br />
willingness to cooperate in a multi-disciplinary team. We specifically <br />
invite applications of women. Among those equally qualified, <br />
handicapped applicants will receive preferential consideration. <br />
International applications are particularly encouraged.<br />
<br />
The successful candidate will be given the opportunity to join the PI <br />
team of the graduate school [https://www.aiphes.tu-darmstadt.de/ "Adaptive Preparation of Information from Heterogeneous Sources" (AIPHES)]. The project conducts innovative <br />
research in a cross-disciplinary context. To that end, methods in <br />
computational linguistics, natural language processing, machine <br />
learning, network analysis, and automated quality assessment are <br />
developed. AIPHES investigates a novel scenario for information <br />
preparation from heterogeneous sources, within the application context <br />
of multi-document summarization. There is close interaction with end <br />
users who prepare textual documents in an online editorial office, and <br />
who should therefore benefit from the results of AIPHES. In-depth <br />
knowledge in one of the above areas is required. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked <br />
among the top ones in respective rankings of German universities. Its <br />
unique [https://www.cedifor.de/en/ "Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences" (CEDIFOR)] emphasizes natural language processing, text mining, machine learning, as well as <br />
scalable infrastructures for assessment and aggregation of knowledge <br />
applied to novel research problems from the Humanities domain. <br />
<br />
Applications should be submitted to <br />
https://public.ukp.informatik.tu-darmstadt.de/irgrecruitment/ by <br />
November 24, 2017 and include a research and teaching statement along <br />
with the CV, publication list, name of three academic references, and <br />
further supporting documents. In case of questions, please contact <br />
Prof. Dr. Iryna Gurevych: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]. The position is open until filled.<br />
<br />
== PostDoc / Senior Researcher, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: PostDoc / Senior Researcher<br />
* Specialty: NLP applications to humanities, social and educational sciences; multimodal analysis and large-scale knowledge extraction<br />
* Location: Darmstadt<br />
* Deadline: November 25, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
PostDoc / Senior Researcher<br />
(for an initial term of two years with an option for an extension)<br />
<br />
to strengthen the group’s expertise in the area of Natural Language Processing with its novel applications to Humanities, Social and Educational Sciences with a focus on multimodal analysis and large-scale knowledge extraction. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP). The group has a strong research profile in computational linguistics, machine learning and text mining. Core research areas include semantic text analysis and resources with their applications in multimodal information processing, knowledge discovery, and discourse analysis. The lab closely cooperates with groups in machine learning, image analysis, and interactive data analytics of the Computer Science department and a large number of research labs worldwide. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization/PhD in Natural Language Processing or Text Mining, preferably with expertise in research and development projects and strong communication skills in English and German (optional). The successful applicant will work on research and development activities within the profile area described above and – based on the previous experience and qualification – will be given an opportunity to contribute to teaching courses, PhD student co-supervision, and project management activities.<br />
<br />
Ideally, the candidates should have demonstrable experience in NLP research, designing and implementing complex (NLP and/or ML) systems, applying Machine Learning incl. neural networks to text processing (e.g. document classification, sequence classification, clustering, etc.), information retrieval and databases, scalable data processing, and strong programming skills in Python and/or Java. <br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by November 25, 2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: interactive text analysis, natural language processing infrastructure<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Text <br />
Analysis and Natural Language Processing Infrastructure. The UKP Lab <br />
is a research group comprising over 30 team members who work on <br />
various aspects of Natural Language Processing (NLP) with a rapidly <br />
developing focus on Interactive Machine Learning, and who provide a <br />
wide range of open source software packages for interactive and <br />
automatic text analysis to research and industry communities.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Natural Language Processing or Text Mining, <br />
preferably with expertise in research and development projects and <br />
strong communication skills in English and German. The successful <br />
applicant will work on research and development activities regarding <br />
text annotation by end-users (researchers, analysts, etc.), <br />
information recommendation, information retrieval, or semantic text <br />
analysis, and to create the corresponding applications and software <br />
components in coordination with the prospective end-users. <br />
<br />
Ideally, the candidates should have demonstrable experience in <br />
designing and implementing complex (NLP and/or ML) systems (frontend <br />
and backend), in applying NLP-related Machine Learning-based methods <br />
(e.g. document classification, sequence classification, clustering, <br />
etc.), experience with information retrieval systems and databases, <br />
scalable data processing, and strong programming skills especially in <br />
Java. Experience with neural network architectures and demonstrable <br />
engagement in open source projects are strong pluses.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Data Analytics” and the Research Training Group “Adaptive <br />
Information Processing of Heterogeneous Content” (AIPHES) funded by <br />
the DFG emphasize NLP, machine learning, text mining and scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members working on common <br />
goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please submit your application via the following form by November 24, <br />
2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The <br />
position is open until filled.<br />
<br />
== KU Leuven, Belgium : Researcher in Automated Reading of Documents ==<br />
<br />
* KU Leuven, Belgium: Postdoc or junior researcher in Automated Reading of Documents <br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral or research fellow<br />
* Specialty: Machine Learning and Natural Language Processing<br />
* Location: Leuven, Belgium<br />
* Deadline: Ongoing, desired start date: as soon as possible <br />
* Date posted: November 1, 2017<br />
* Contact: [mailto:sien.moens@cs.kuleuven.be Prof. Marie-Francine Moens]<br />
<br />
'''Researcher in Automated Reading of Documents''' <br/><br />
(Department of Computer Science, KU Leuven, Belgium)<br />
<br />
The Language Intelligence & Information Retrieval lab (https://liir.cs.kuleuven.be) that is part of the Human Computer Interaction group of the Department of Computer Science of KU Leuven in Belgium has an open position for a motivated researcher interested in the latest developments in artificial intelligence for the automated reading of documents. <br />
<br />
The research is carried out in the frame of the SaaS project (Self-learning SaaS platform for simplification of data-intensive customer experiences). The goal is to design, develop and test novel machine learning models that are self-learning and that can be applied for real-time processing of unstructured or semi-structured documents. Special attention will go to deep learning models relying on character-based or word-based representations of content. <br />
<br />
We offer a research position in a research team that has an outstanding international reputation in natural language processing and understanding, multimedia mining, machine learning and information retrieval. Within the team we study both theoretical modelling and challenging applications. We investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. We have a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, user generated content mining, and web mining and search. KU Leuven is located about 25 kilometers from Brussels, the capital of Europe. For the second year in a row, KU Leuven leads the Reuters ranking as Europe’s most innovative university. <br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field.<br />
* Research experience in machine learning.<br />
<br />
'''Desired'''<br />
* Good knowledge of the English language and some knowledge of French or Dutch.<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds.<br />
* Desired start date: as soon as possible.<br />
* Competitive salary. <br />
<br />
'''How to Apply''' <br/><br />
If interested, send your CV and motivation letter to Prof. Marie-Francine Moens (sien.moens@cs.kuleuven.be). The position will be filled in as soon as possible.<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Spring/Summer 2018<br />
* Date posted: October 31, 2017<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting Spring or Summer 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is Spring 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder''' <br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
== Two Postdoctoral Positions on Interpretable Vector Space Models ==<br />
*Employer: Cardiff University<br />
*Title: Postdoctoral research associate<br />
*Speciality: Neural networks, statistical relational learning, natural language processing<br />
*Location: Cardiff, UK<br />
*Deadline: November 2 2017<br />
*Date posted: October 6, 2017<br />
*Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC). The overall aims of this project are (i) to learn interpretable vector space representations of entities and their relationships, and (ii) to exploit these vector space representations for various forms of flexible reasoning with, and learning from structured data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
The aim of these positions will be to contribute to one or more of the following topics.<br />
<br />
1) Learning structured event embeddings. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with cognitively inspired representations (e.g. based on the theory of conceptual spaces). Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. <br />
<br />
2) Combining statistical relational learning with vector space models of commonsense reasoning. Low-dimensional vector space representations can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning (SRL) can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths, enabling interpretable and robust plausible reasoning from sparse relational data.<br />
<br />
3) Geometric representations of logical theories. Most vector space models for knowledge base completion simply represent entities, attributes and relations as vectors. In many domains, however, plausible inferences rely on complex dependencies that cannot be captured by such representations. As an alternative, we will develop methods in which predicates are represented as regions, and logical formulas correspond to qualitative constraints on the spatial configurations of these regions. This model will support more complex inferences than existing approaches, will allow us to exploit existing domain knowledge when learning vector space representations, and will conversely allow us derive approximate logical theories from a learned embedding.<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Salaried 4-year PhD Position in Computational Linguistics/NLP at Stockholm University ==<br />
*Employer: Stockholm University, Sweden<br />
*Title: PhD candidate<br />
*Speciality: Computational Linguistics/Natural Language Processing<br />
*Location: Stockholm, Sweden<br />
*Deadline: October 16, 2017<br />
*Date posted: September 20, 2017<br />
*Contact: [mailto:robert@ling.su.se Robert Östling]<br />
<br />
More information and application form: http://www.su.se/english/about/working-at-su/jobs?rmlang=UK&rmpage=job&rmjob=3869<br />
<br />
The Department of Linguistics at Stockholm University is looking for a new PhD candidate in the area of computational linguistics/natural language processing. PhD candidates are regular employees of Stockholm University, with a starting salary of 25,300 SEK (2,650 EUR; 3,200 USD) per month and the same benefits and social security as other University employees. The position is fully funded for 4 years. Extension up to one year is possible if the candidate performs teaching or other duties at the department, and further extension is granted in case of parental or sick leave.<br />
<br />
The choice of thesis topic is not restricted to a particular project, but should be aligned with the research profile of the department. Possible topics include multilingual NLP methods, machine translation, or computational methods for other areas of research at the department (language acquisition, linguistic typology, phonetics, sign language).<br />
<br />
Potential applicants are encouraged to contact [mailto:robert@ling.su.se Robert Östling] to discuss possible thesis projects, or other issues related to the position.<br />
<br />
== Tenure Line Assistant Professor Position in Linguistics at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Tenure Line Assistant Professor Position in Linguistics at Northwestern University<br />
*Speciality: Meaning<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2017<br />
*Date posted: September 18, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
http://www.linguistics.northwestern.edu/about/news/faculty-search.html<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line assistant professor position with a start date of September 1, 2018. We are looking for candidates with research and teaching interests in meaning, broadly construed. We are particularly interested in candidates whose research program includes cognitive, computational, and/or social approaches. The successful candidate will join a vibrant interdisciplinary community of researchers in the science of language, including computer science, philosophy, psychology, cognitive neuroscience, and speech science.<br />
<br />
To receive fullest consideration, applications should be uploaded by December 1, 2017. Candidates must hold a Ph.D. in Linguistics, Cognitive Science, Computer Science, Psychology, or a related field by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work, teaching evaluations (if available), and the names of three references (with their contact information). References will separately receive upload instructions after you have submitted your application (letters of reference should arrive as close as December 1st as possible).<br />
<br />
The Department is strongly committed to enhancing diversity, equity and inclusion in all aspects – including, but not limited to, race/ethnicity, and gender, as well as disability, sexual orientation, and gender expression and identity. We encourage applications from candidates that share this vision.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair.<br />
<br />
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=People&diff=12150People2018-01-21T21:55:28Z<p>Tristan Miller: /* M */ [https://logological.org/ Miller, Tristan] - Technische Universität Darmstadt</p>
<hr />
<div>This is a list of homepages of researchers in Computational Linguistics, in the form '''last name, first name - affiliation'''. <br />
<br />
See also [[Academic genealogy]], the genealogy of people with academic degrees, based on graduate supervisors being 'parents' and their graduate students being 'children'.<br />
<br />
== A ==<br />
<br />
*[http://littera.deusto.es/prof/abaitua Abaitua, Joseba] - Universidad de Deusto<br />
*[http://tony.abou-assaleh.net Abou-Assaleh, Tony] - Dalhousie University<br />
*[http://www-personal.umich.edu/~ladamic/ Adamic, Lada] - University of Michigan<br />
*[http://www.cond.org/ Adar, Eytan] - University of Washington<br />
*[http://www.dfki.de/~janal/ Alexandersson, Jan] - German Research Center for Artificial Intelligence<br />
*[http://www.ics.uci.edu/~boris Aleksandrovsky, Boris] UC Irvine<br />
*[http://www-scf.usc.edu/~alcazar/ Alcázar, Asier] - University of Southern California<br />
*[http://alfonseca.org/ Alfonseca, Enrique] - Google<br />
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000808989 Alegria, Iñaki] - University of the Basque Country<br />
*[http://www.dfki.de/~janal/ Alexandersson, Jan] German Research Center for Artificial Intelligence<br />
*[http://www.cs.rochester.edu/u/james/ Allen, James] - University of Rochester<br />
*[http://www.dc.fi.udc.es/~alonso/ Alonso, Miguel A.]<br />
*[http://www.wasifaltaf.com Altaf, Wasif] - University of Bonn<br />
*[http://www.linguist.jussieu.fr/~amsili/ Amsili, Pascal] - University of Paris 7 - Denis Diderot<br />
*[http://www.aueb.gr/users/ion/ Androutsopoulos, Ion] - Athens University of Economics and Business<br />
*[http://clwww.essex.ac.uk/~doug/ Arnold, Doug] Univ. of Essex<br />
*[http://www.ai.sri.com/~appelt/ Appelt, Doug ] SRI International<br />
*[http://korpus.dsl.dk/staff/ja/ Asmussen, Jörg] - DSL - Society for Danish Language and Literature, Copenhagen<br />
*[http://www.carleton.ca/~asudeh/ Asudeh, Ash] - Carleton University <br />
*[http://www.coli.uni-sb.de/~tania/ Avgustinova, Tania] - Universität des Saarlandes<br />
<br />
== B ==<br />
<br />
*[http://www.cs.cmu.edu/~klb Baker, Kathryn] - Carnegie Mellon University<br />
*[http://comp.ling.utexas.edu/jbaldrid/ Baldridge, Jason] - University of Texas at Austin<br />
*[http://www.cs.mu.oz.au/~tim/ Baldwin, Timothy] - University of Melbourne<br />
*[http://www.georgetown.edu/cball/cball.html Ball, Catherine] - Georgetown University<br />
*[http://www.cs.cmu.edu/~banerjee Banerjee, Satanjeev] - Carnegie Mellon University<br />
*[http://www.lsi.upc.es/~batalla Batalla,Jordi Atserias] - UPC, Spain<br />
*[http://www5.informatik.uni-erlangen.de/Personen/batliner/ Batliner, Anton] - Friedrich-Alexander-Universität Erlangen-N&uuml;rnberg<br />
*[http://www.dfki.de/~becker Becker, Tilman] - DFKI Saarbruecken, Germany<br />
*[http://faculty.washington.edu/ebender Bender, Emily] - University of Washington<br />
*[http://homepages.infoseek.com/~corpuslinguistics/homepage.html Berber,Tony] Sardinha<br />
*[http://richard.bergmair.eu/ Bergmair, Richard] University of Cambridge<br />
*[http://wortschatz.uni-leipzig.de/~cbiemann/ Biemann, Chris] - University of Leipzig, Germany<br />
*[http://www.dai.ed.ac.uk/students/kimb Binsted, Kim] University of Edinburgh<br />
*[http://www.cs.mu.oz.au/~sb/ Bird, Steven] - University of Melbourne<br />
*[http://seneca.uab.es/filfrirom/Blanco.html Blanco, Xavier] - Autonomous University of Barcelona<br />
*[http://www.pdg.cnb.uam.es/blaschke/personalPage.html Blaschke, Christian]<br />
*[http://www.dcs.shef.ac.uk/~kalina/ Boncheva, Kalina] Univ. of Sheffield]<br />
*[http://www.dcs.shef.ac.uk/~kalina/ Bontcheva, Kalina] - Univ. of Sheffield<br />
*[http://www3.ntu.edu.sg/home/fcbond/ Bond, Francis] - Nanyang Technological University, Singapore<br />
*[http://www.let.rug.nl/bos/ Bos, Johan] - University of Groningen<br />
*[http://www.iro.umontreal.ca/~boufaden/ Boufaden, Narjès] - University of Montreal<br />
*[http://www.let.rug.nl/~gosse Bouma, Gosse] - University of Groningen<br />
*[http://www.nyu.edu/projects/bowman Bowman, Sam] - New York University<br />
*[http://www.di.fc.ul.pt/~ahb/ Branco, Antonio] - University of Lisbon<br />
*[http://www.karlbranting.net Branting, Karl]<br />
*[http://coli.uni-sb.de/~thorsten Brants, Thorsten] - University of Saarland<br />
*[http://www.coli.uni-sb.de/~brawer Brawer, Sascha] - University of the Saarland<br />
*[http://www.cs.cornell.edu/~ebreck Breck, Eric] - Cornell University<br />
*[http://clwww.essex.ac.uk/~andrewb/ Bredenkamp, Andrew]<br />
*[http://www.csse.monash.edu.au/~jwb/ Breen, Jim] - Monash University<br />
*[http://www.cog.jhu.edu/faculty/brent.html Brent,Michael R.] Johns Hopkins University<br />
*[http://www.informatik.uni-leipzig.de/~brewka/ Brewka] - Gerhard, University of Leipzig<br />
*[http://www.xsoft.com/ Breyman, Clark] Xerox Linguistic Technologies<br />
*[http://research.microsoft.com/%7Ebrill/ Brill, Eric] - Microsoft Research<br />
*[http://www.cl.cam.ac.uk/users/ejb/ Briscoe, Ted] - University of Cambridge<br />
*[http://www.dfki.de/~paulb Buitelaar, Paul] - DFKI<br />
*[http://www.cs.utexas.edu/users/razvan/ Bunescu, Razvan] - University of Texas at Austin<br />
<br />
== C ==<br />
<br />
*[http://www.hinocatv.ne.jp/~price/ Caldwell, Price] - Meisei University<br />
*[http://www.acs.ilstu.edu/faculty/mecalif/calif.htm Califf,Mary Elaine] - Illinois State University<br />
*[http://ilk.uvt.nl/~sander/ Canisius, Sander] - Tilburg University<br />
*[http://www.cis.upenn.edu/~cliff-group/94/carberry.html Carberry, Sandra] - Univ. of Delaware, Univ. of Pennsylvania<br />
*[http://www.cs.cornell.edu/Info/Faculty/Claire_Cardie.html Cardie, Claire] - Cornell University<br />
*[http://www.cogs.susx.ac.uk/lab/nlp/carroll/carroll.html Carroll, John] - University of Sussex<br />
*[http://jones.ling.indiana.edu/~dcavar Cavar, Damir] - Indiana University, Bloomington<br />
*[http://tantek.com/map.html Celik, Tantek] - Technorati<br />
*[http://cer.freeshell.org Cer, Daniel] - University of Colorado at Boulder<br />
*[http://nlp.changwon.ac.kr/~jcha/ Cha, Jeongwon] - Changwon National University<br />
*[http://www.cs.uleth.ca/~chali Chali, Yllias] - University of Lethbridge<br />
*[http://www.cs.brown.edu/people/ec/home.html Charniak, Eugene] - Brown University<br />
*[http://iit-iti.nrc-cnrc.gc.ca/personnel/chen_boxing_e.html Chen, Boxing] - National Research Council<br />
*[http://www.ciscl.unisi.it/persone/chesi.htm Chesi, Cristiano] - CISCL, University of Siena<br />
*[http://www.isi.edu/~chiang Chiang, David] - USC Information Sciences Institute<br />
*[http://www.alphabit.net/Docente/docente_eng.htm Chiari, Isabella] - University "La Sapienza" of Rome<br />
*[http://korterm.kaist.ac.kr/kschoi/ Choi, Key-Sun] - Korea Advanced Institute of Science and Technology<br />
*[http://web.mit.edu/afs/athena.mit.edu/org/l/linguistics/www/chomsky.home.html Chomsky, Noam] - MIT<br />
*[http://research.microsoft.com/users/church/ Church, Kenneth] - Microsoft Research<br />
*[http://www.dcs.shef.ac.uk/~fabio/ Ciravegna, Fabio] - University of Sheffield<br />
*[http://web.comlab.ox.ac.uk/oucl/work/stephen.clark/ Clark, Stephen] - University of Oxford<br />
*[http://compbio.uchsc.edu/Hunter_lab/Cohen Cohen, Kevin Bretonnel] - U. Colorado School of Medicine<br />
*[http://people.csail.mit.edu/u/m/mcollins/public_html/ Collins, Michael] - MIT Computer Science and Artificial Intelligence Laboratory<br />
*[http://www.cl.cam.ac.uk/users/aac10/ Copestake, Ann] - University of Cambridge<br />
*[http://lands.let.kun.nl/TSpublic/coppen Coppen, Peter-Arno] - University of Nijmegen, The Netherlands<br />
*[http://plg.uwaterloo.ca/~gvcormac/ Cormack, Gordon] - University of Waterloo<br />
*[http://www.psych.qub.ac.uk/staff/teaching/cowie/index.aspx Cowie, Roddy] - Queen's University, Belfast<br />
*[http://www.biostat.wisc.edu/~craven/ Craven, Mark] - University of Wisconsin<br />
*[http://www2.ulster.ac.uk/staff/n.creaney.html Creaney, Norman] - University of Ulster<br />
*[http://www.dia.uniroma3.it/~crescenz/ Crescenzi, Valter] - Università Roma Tre<br />
*[http://thor.info.uaic.ro/~dcristea/ Cristea, Dan] - University of Iasi<br />
*[http://www.harlequin.com/ Crowe, Jeremy] - Harlequin Ltd.<br />
*[http://www.dcs.shef.ac.uk/~hamish Cunningham, Hamish] - University of Sheffield<br />
*[http://www-users.cs.york.ac.uk/~jc/ Cussens, James] - University of York<br />
<br />
== D ==<br />
*[http://www.clips.uantwerpen.be/~walter/ Daelemans, Walter] - University of Antwerp<br />
*[http://www.cs.biu.ac.il/~dagan/ Dagan, Ido] - Bar Ilan University, Israel<br />
*[http://conversational-technologies.com Dahl, Deborah] - Conversational Technologies<br />
*[http://stl.recherche.univ-lille3.fr/sitespersonnels/dal/index.html Dal, Georgette] - Universite de Lille<br />
*[http://www.ics.mq.edu.au/~rdale Dale, Robert] - Centre for Language Technology, Macquarie University<br />
*[http://www.cs.utah.edu/~hal/ Daumé III, Hal] - University of Utah<br />
*[http://davies-linguistics.byu.edu Davies, Mark] - Brigham Young University<br />
*[http://cs.haifa.ac.il/~edaya Daya, Ezra] - NICE Systems Ltd.<br />
*[http://www.csi.uottawa.ca/~delannoy Delannoy, Jean-Francois] - University of Ottawa<br />
*[http://www.uqtr.uquebec.ca/~delisle/index.html Delisle, Sylvain] UQTR<br />
*[http://comp.ling.utexas.edu/denis Denis, Pascal] - University of Texas at Austin<br />
*[http://www.math.bas.bg/~iad/ Derzhanski, Ivan] - Bulgarian Academy of Sciences<br />
*[http://www.ling.ohio-state.edu/~dm/ Detmar Meurers, Walt] - The Ohio State University Linguistics Dept.<br />
*[http://www.limsi.fr/Individu/devil/ Devillers, Laurence] - LIMSI<br />
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000808994 Díaz de Ilarraza, Arantza] - University of Basque Country<br />
*[http://www.cs.umd.edu/users/bonnie/ Dorr, Bonnie] - University of Maryland<br />
*[http://www.nyu.edu/pages/linguistics/doughert.html Dougherty, Ray] - New York University<br />
*[http://www.ai.sri.com/~dowding Dowding, John] - SRI<br />
*[http://www.pcug.org.au/~jdowling/ Dowling, Jason] PC Users Group ACT Inc., Canberra, Australia<br />
<br />
== E ==<br />
<br />
*[http://www.uni-bielefeld.de/lili/personen/cebert/ Ebert, Christian] - University of Bielefeld<br />
*[http://www.ims.uni-stuttgart.de/~eckle/ Eckle-Kohler, Judith]<br />
*[http://www.philipedmonds.com/ Edmonds, Philip] - University of Toronto<br />
*[http://cs.jhu.edu/~jason Eisner, Jason] - Johns Hopkins University<br />
*[http://www.cs.bgu.ac.il/~elhadad/ Elhadad, Michael] - Ben-Gurion University of the Negev<br />
*[http://www.cogsci.ed.ac.uk/~marke/ Ellison, T. Mark] - University of Edinburgh<br />
*[http://www.ik.fh-hannover.de/ik/person/ben/ben.htm Endres-Niggemeyer, Brigitte] FH Hannover<br />
*[http://www.sciences.univ-nantes.fr/info/perso/permanents/enguehard/ Enguehard, Chantal] - Laboratoire d'Informatique de Nantes Atlantique<br />
*[http://coli.uni-sb.de/~erbach/ Erbach, Gregor] - Universität des Saarlandes<br />
*[http://nl.ijs.si/et/ Erjavec, Tomaz]<br />
*[http://comp.ling.utexas.edu/erk/ Erk, Katrin] - University of Texas at Austin<br />
*[http://www.cogsci.uni-osnabrueck.de/~severt/ Evert, Stefan] - University of Osnabrück<br />
<br />
== F ==<br />
<br />
*[http://slt.wcl.ee.upatras.gr/Fakotakis/personal.htm Fakotakis, Nikos] - University of Patras<br />
*[http://www.phon.ucl.ac.uk/home/alex/home.htm Fang, Alex Chengyu] - University College London<br />
*[http://www.purl.org/net/fa Feldman, Anna] - Montclair State University<br />
*[http://wordnet.princeton.edu/~fellbaum/ Fellbaum, Christiane] - Princeton University<br />
*[http://ling.cuc.edu.cn/htliu/feng/feng.htm Feng, Zhiwei] - IAL of China<br />
*[http://staff.science.uva.nl/~raquel/ Fernandez, Raquel] - ILLC, University of Amsterdam<br />
*[http://www.cs.umbc.edu/~finin/ Finin, Tim] - University of Maryland, Baltimore County (UMBC)<br />
*[http://lingo.stanford.edu/dan/ Flickinger, Dan] - CSLI, Stanford University<br />
*[http://www.dlsi.ua.es/~mlf/ Mikel Forcada] - Universitat d'Alacant<br />
*[http://www.cse.ohio-state.edu/~fosler Fosler-Lussier, Eric] - The Ohio State University<br />
*[http://www.coli.uni-saarland.de/~fouvry/ Fouvry, Frederik]<br />
*[http://www.cs.brown.edu/people/hjf/ Fox, Heidi] - Brown University, Metacarta<br />
*[http://www.cs.technion.ac.il/~francez Francez, Nissim] - Technion, Israel<br />
*[http://www.cs.cmu.edu/~ref/ Frederking, Robert] - Carnegie-Mellon University<br />
*[http://www.ee.ust.hk/~pascale/ Fung, Pascale] - Hong Kong University of Science and Technology<br />
<br />
== G ==<br />
<br />
*[http://www.cs.technion.ac.il/~gabr Gabrilovich, Evgeniy]<br />
*[http://www.dcs.shef.ac.uk/~robertg/ Gaizauskas, Rob] - University of Sheffield<br />
*[http://www.sics.se/~gamback/ Gamback, Bjorn] - Swedish Institute of Computer Science<br />
*[http://www.dai.ed.ac.uk/students/narcisbg Gardella, Narcis Bassols] Univ. of Edinburgh<br />
*[http://www.coli.uni-sb.de/~claire/ Gardent, Claire] Universit&auml;t des Saarlandes<br />
*[http://www.gelbukh.com/ Gelbukh, Alexander] - CIC-IPN<br />
*[http://www.isi.edu/natural-language/people/germann/ Germann, Ulrich] - ISI<br />
*[https://netfiles.uiuc.edu/girju/index.html Girju, Roxana] - University of Illinois, Urbana-Champaign<br />
*[http://tcc.itc.it/people/giuliano.html Giuliano, Claudio] - ITC-irst<br />
*[http://www.uni-salzburg.at/portal/page?_pageid=425,405845&_dad=portal&_schema=PORTAL Goebl, Hans] - Univeristät Salzburg<br />
*[http://www.cs.ucf.edu/~gomez Gomez, Fernando] ucf<br />
*[http://www.esi.uem.es/~jmgomez Gomez-Hidalgo, Jose-Maria] - UEM<br />
*[http://www.linguistics.ucsb.edu/faculty/stgries/ Gries, Stefan Th.] - UCSB<br />
*[http://cs.nyu.edu/cs/faculty/grishman/ Grishman, Ralph] - New York University<br />
*[http://das-www.harvard.edu/users/faculty/Barbara_Grosz/Barbara_Grosz.html Grosz, Barbara] - Harvard University<br />
*[http://www-ksl.stanford.edu/people/gruber/ Gruber, Tom] - Stanford University<br />
*[http://www.cs.duke.edu/~cig Guinn, Curry I.] - Duke U.<br />
*[http://www.ukp.tu-darmstadt.de/ Gurevych, Iryna] - Darmstadt University of Technology<br />
*[http://www.cs.bilkent.edu.tr/~guvenir/guvenir.html Guvenir, Altay] - Bilkent University<br />
<br />
== H ==<br />
<br />
*[http://www.swan.ac.uk/french/web-content/staff/p-ten-hacken.html Hacken, Pius ten] - Swansea University<br />
*[http://www.coling.uni-freiburg.de/~hahn/hahn.html Hahn, Udo] - University of Freiburg<br />
*[http://ufal.mff.cuni.cz/~hajic Hajič, Jan] - Charles University in Prague<br />
*[http://www.linkedin.com/in/aaronhan Han, Aaron Li-Feng] - University of Macau<br />
*[http://www.comp.nus.edu.sg/~cuihang Hang, Cui] - National University of Singapore<br />
*[http://www.coli.uni-sb.de/~hansen Hansen-Schirra, Silvia] - Universität des Saarlandes<br />
*[http://renoir.vill.edu/faculty/hardt/html/home.html Hardt, Daniel] Villanova University<br />
*[http://128.147.244.54/dbmi/profile.cfm?ID=23751 Harkema, Henk] - University of Pittsburgh<br />
*[http://pi7.fernuni-hagen.de/hartrumpf/ Hartrumpf, Sven] - University of Hagen, Germany<br />
*[http://www.cis.udel.edu/~harvey/ Harvey, Terry]<br />
*[http://www.linguistik.uni-erlangen.de/~rrh/ Hausser, Roland] - University of Erlangen, Germany<br />
*[http://www.sims.berkeley.edu/~hearst Hearst, Marti] - UC Berkeley<br />
*[http://www.cse.ogi.edu/~heeman Heeman, Peter] - OGI<br />
*[http://homepages.inf.ed.ac.uk/jhender6/ Henderson, James] - University of Edinburgh<br />
*[http://www.asp.ogi.edu/~hynek/ Hermansky, Hynek] - Oregon Graduate Institute of Science and Technology<br />
*[http://www.isi.edu/~ulf/ Hermjakob, Ulf] - USC/ISI<br />
*[http://www.esi.uem.es/~jmgomez/ Hidalgo, José María Gómez] - Universidad Europea de Madrid<br />
*[http://www.ifi.unizh.ch/staff/hess.html Hess, Michael] - Univ. of Zurich, Switzerland<br />
*[http://www.cs.toronto.edu/~gh Hirst, Graeme] - University of Toronto<br />
*[http://www.isi.edu/~hobbs/ Jerry Hobbs] - USC/ISI<br />
*[http://www.cs.cmu.edu/~chogan Hogan, Christopher] - Carnegie-Mellon University<br />
*[http://www.isi.edu/natural-language/people/hovy.html Hovy, Eduard] - ISI<br />
*[http://ist-socrates.berkeley.edu/~jcl2/churen.htm Huang, Chu-Ren] - Academica Sinica<br />
*[http://www.cs.ucf.edu/~hull Hull, Richard] - University of Central Florida<br />
*[http://compbio.uchsc.edu/Hunter_lab/Hunter Hunter, Larry] - U. Colorado School of Medicine<br />
*[http://datamining.typepad.com/data_mining/ Hurst, Matthew] - BuzzMetrics<br />
*[http://ourworld.compuserve.com/homepages/WJHutchins/ Hutchins, John]<br />
*[http://www.cs.pitt.edu/~hwa Hwa, Rebecca] - University of Pittsburgh<br />
<br />
== I ==<br />
<br />
== J ==<br />
<br />
*[http://www.cis.upenn.edu/~cliff-group/94/pjacobs.html Jacobs, Paul] - General Electric<br />
*[http://www.stanford.edu/~tiflo Jaeger, T. Flroian] - Stanford University<br />
*[http://ist.psu.edu/faculty_pages/jjansen/ Jansen, Jim] - Penn State<br />
*[http://www.cs.nyu.edu/~hengji Ji, Heng] - New York University<br />
*[http://www.cog.brown.edu/~mj Johnson, Mark] - Brown University<br />
*[http://www.cogsci.ed.ac.uk/~bernie/ Jones, Bernie] University of Edinburgh<br />
*[http://www.ida.liu.se/~arnjo/ Jönsson, Arne] - Linkoping University<br />
<br />
== K ==<br />
*[http://cs.joensuu.fi/~tkakkone Kakkonen, Tuomo] - University of Joensuu<br />
*[http://www.ai.sri.com/~megumi Kameyama, Megumi] - SRI International<br />
*[http://www.comp.nus.edu.sg/~kanmy Kan, Min-Yen] - National University of Singapore<br />
*[http://users.utu.fi/karhumak/ Karhumaki, Juhani] - University of Turku<br />
*[http://www.sics.se/~jussi/ Karlgren, Jussi] - SICS, Sweden<br />
*[http://www2.parc.com/istl/members/karttune/ Karttunen, Lauri]<br />
*[http://elex.amu.edu.pl/ifa/staff/kaszubski.html Kaszubski, Przemys&#322;aw] - Adam Mickiewicz University<br />
*[http://www.cs.utexas.edu/users/rjkate/ Kate, Rohit J.] - University of Texas at Austin<br />
*[http://www-users.cs.york.ac.uk/~kazakov/ Kazakov, Dimitar] - University of York<br />
*[http://homepages.inf.ed.ac.uk/keller/ Keller, Frank] - University of Edinburgh<br />
*[http://www.cs.dal.ca Keselj, Vlado] Dalhousie University<br />
*[http://www.mabidkhan.com/ Khan, Abid] - University of Peshawar, Pakistan<br />
*[http://www.itri.bton.ac.uk/~Adam.Kilgarriff Kilgarriff, Adam] - University of Brighton<br />
*[http://www.cs.wisc.edu/~sklein/sklein.html Klein, Sheldon] - University of Wisconsin<br />
*[http://www.isi.edu/~knight/ Knight, Kevin] - ISI<br />
*[http://www.ims.uni-stuttgart.de/~kobdani/ Kobdani, Hamidreza] - University of Stuttgart<br />
*[http://www.iccs.inf.ed.ac.uk/~pkoehn/ Koehn, Philipp] - University of Edinburgh<br />
*[http://svenska.gu.se/~svedk Kokkinakis, Dimitrios] - Göteborg University<br />
*[http://www.cs.ualberta.ca/~kondrak/ Kondrak, Grzegorz] - University of Alberta<br />
*[http://www.coli.uni-saarland.de/~kordoni/ Kordoni, Valia] - Universität des Saarlandes<br />
*[http://www.kornai.com/ Kornai, Andras]<br />
*[http://www.ling.helsinki.fi/~koskenni/ Koskenniemi, Kimmo] - University of Helsinki<br />
*[http://users.encs.concordia.ca/~kosseim/ Kosseim, Leila] - Concordia University, Montreal<br />
*[http://www.dlsi.ua.es/~zkozareva/ Kozareva, Zornitsa] - University of Alicante<br />
*[http://dis.tpd.tno.nl/mmts/wessel_kraaij.html Kraaij, Wessel] - TNO<br />
*[http://www-sk.let.uu.nl Krauwer, Steven, ELSNET] - Utrecht University<br />
*[http://external.nj.nec.com/homepages/krovetz/ Krovetz, Robert] NEC<br />
*[http://www.peter-kuehnlein.net/ Kuehnlein, Peter] - University of Groningen<br />
*[http://jones.ling.indiana.edu/~skuebler/ Kuebler, Sandra] - Indiana University, Bloomington<br />
*[http://www.jkk.name/ Kummerfeld, Jonathan K.] - University of Michigan<br />
*[http://www.cs.ucd.ie/staff/nick/ Kushmerick, Nicholas] - University College, Dublin<br />
<br />
== L ==<br />
<br />
*[http://www.ling.gu.se/~lager/ Lager, Torbjörn] - Göteborg University<br />
*[http://www.ict.csiro.au/staff/Andrew.Lampert/ Lampert, Andrew] - CSIRO ICT Centre / Macquarie University<br />
*[http://www.cs.cmu.edu/~ianlane/ Lane, Ian] - Carnegie Mellon University<br />
*[http://hlt.fbk.eu/en/people/lavelli/ Lavelli, Alberto] - FBK-IRST<br />
*[http://www-personal.umich.edu/~jlawler/index.html Lawler, John] - University of Michigan<br />
*[http://nlp.postech.ac.kr/~gblee Lee, Geunbae] - POSTECH<br />
*[http://www.cs.cornell.edu/home/llee Lee, Lillian] - Cornell University<br />
*[http://www.cs.bham.ac.uk/~mgl Lee, Mark] - University of Birmingham<br />
*[http://www.ling.lancs.ac.uk/staff/geoff/geoff.htm Leech, Geoffrey] - Professor LAMEL, Lancaster University, UK<br />
*[http://jochenleidner.com/ Leidner, Jochen L.] - Research Scientist, Thomson Reuters Corporation<br />
*[http://sites.google.com/site/olemon Lemon, Oliver] - Heriot-Watt University<br />
*[http://www.ilc.cnr.it/~lenci/ Lenci, Alessandro] - Università di Pisa<br />
*[http://people.cs.uchicago.edu/~levow/ Levow, Gina-Anne] - University of Chicago<br />
*[http://www.cc.gatech.edu/~baoli/ Li, Baoli] - Georgia Institute of Technology<br />
*[http://www1.i2r.a-star.edu.sg/~hli/ Li, Haizhou] - Institute for Infocomm Research, Singapore<br />
*[http://www.ling.upenn.edu/~myl/ Liberman, Mark] - University of Pennsylvania<br />
*[http://www.isi.edu/~cyl/ Lin, Chin-Yew] USC/ISI<br />
*[http://www.cs.ualberta.ca/~lindek/ Lin, Dekang] - University of Alberta<br />
*[http://htliu.yeah.net/ Liu, Haitao] - Communication University of China<br />
*[http://nlp.ict.ac.cn/~liuqun/index_en.htm Liu, Qun] - Institute of Computing Technology, CAS<br />
*[http://mtgroup.ict.ac.cn/~liuyang/ Liu, Yang] - Institute of Computing Technology, CAS<br />
*[http://ufal.mff.cuni.cz/~lopatkova Lopatková, Markéta] Charles University in Prague<br />
*[http://terra.di.fct.unl.pt/~gpl/ Lopes, Gabriel] New University of Lisbon<br />
*[http://www.langnat.com/~loupy/index-en.html Loupy, Claude de] - Universite de Paris X Nanterre<br />
*[http://www.personal.psu.edu/xxl13 Lu, Xiaofei] - Pennsylvania State University<br />
<br />
== M ==<br />
<br />
*[http://www.soi.city.ac.uk/~andym/ MacFarlane, Andrew] - City University of London<br />
*[http://www.desilinguist.org Madnani, Nitin] - Educational Testing Service<br />
*[http://www-cs-students.Stanford.EDU/~magerman Magerman, David] - Stanford University<br />
*[http://tcc.itc.it/people/magnini.html Magnini, Bernardo] - ITC-IRST<br />
*[http://www.karacaymalkar.com Malkar, Karacay] - Webportal<br />
*[http://www.rohan.sdsu.edu/~malouf Malouf, Rob] - San Diego State University<br />
*[http://www.sultry.arts.usyd.edu.au/ Manning, Christopher] - University of Sydney<br />
*[http://www.demarcken.org/carl/ de Marcken, Carl] ITA Software<br />
*[http://www.isi.edu/~marcu/ Marcu, Daniel] - USC/ISI<br />
*[http://overstated.net/about Marlow, Cameron] - Yahoo! Research<br />
*[http://www.limsi.fr/Individu/martin/ Martin,Jean-Claude] - LIMSI<br />
*[http://www.yorku.ca/jmason/ Mason, James A.] - York University<br />
*[http://www.ics.mq.edu.au/~mpawel Mazur, Pawel] - Wroclaw University of Technology and Macquarie University<br />
*[http://www.informatics.susx.ac.uk/research/nlp/mccarthy/mccarthy.html McCarthy, Diana] - University of Sussex<br />
*[http://homepages.inf.ed.ac.uk/mmcconvi McConville, Mark] - University of Edinburgh<br />
*[http://alum.mit.edu/www/davidmcdonald/ McDonald, David] - Smart Information Flow Technologies (SIFT)<br />
*[http://www.cs.columbia.edu/~kathy McKeown, Kathy] Columbia University<br />
*[http://www.eecis.udel.edu/~mccoy/ McKoy, Kathy] - University of Delaware<br />
*[http://stp.lingfil.uu.se/~bea Megyesi, B. Beata] - Uppsala University<br />
*[http://cs.nyu.edu/~melamed Melamed, I. Dan] - New York University<br />
*[http://www.gabormelli.com Melli, Gabor] - PredictionWorks Inc.<br />
*[http://www.latl.unige.ch/personal/paola.html Merlo, Paola] - University of Geneva<br />
*[http://www.ling.ohio-state.edu/~dm/ Meurers, Walt Detmar] OH State Linguistics<br />
*[http://www.csse.uwa.edu.au/~fontor/ Midgley, T. Daniel] - University of Western Australia<br />
*[http://www.cs.unt.edu/~rada Mihalcea, Rada] - University of North Texas<br />
*[https://logological.org/ Miller, Tristan] - Technische Universität Darmstadt<br />
*[http://www.cis.upenn.edu/~elenimi/ Miltsakaki, Eleni] - University of Pennsylvania<br />
*[http://www.ics.mq.edu.au/~mariam Milosavljevic, Maria] - Macquarie University<br />
*[http://coli.uni-sb.de/~mineur Mineur, Anne-Marie] University of the Saarland / Utrecht University<br />
*[http://imaginarycartography.com/work.html Minor, Joshua T.] - Cataphora, Inc.<br />
*[http://staff.science.uva.nl/~gilad/ Mishne, Gilad] - University of Amsterdam<br />
*[http://www.wlv.ac.uk/~le1825/main.html Mitkov, Ruslan] - University of Wolverhampton<br />
*[http://www.let.rug.nl/~begona/ Moirón, Begoña Villada] - University of Groningen<br />
*[http://www.ifi.unizh.ch/~molla/ Molla-Aliod, Diego] - University of Zurich<br />
*[http://www.dcs.qmul.ac.uk/~christof/ Monz, Christof] - University of Amsterdam (ILLC)<br />
*[http://www.cs.utexas.edu/users/mooney/ Mooney, Raymond J.] - University of Texas at Austin<br />
*[http://www.signiform.com/erik/ Mueller, Erik] - IBM Research<br />
*[http://www.xn--stefan-mller-klb.net/ Müler, Stefan] - Universität Bremen<br />
*[http://www.ukp.tu-darmstadt.de/people/mueller/ Müller, Christof] - Darmstadt University of Technology<br />
*[http://www.dlsi.ua.es/eines/membre.cgi?id=eng&nom=rafael&tipus=pdi Muñoz, Rafael] - University of Alicante<br />
*[http://www.puran.info Malik, Abbas] - GETALP - LIG, Université de Grenoble<br />
<br />
== N ==<br />
<br />
*[http://www.cs.utexas.edu/users/ai-lab/people/grad/nahm.html Nahm, Un Yong] - University of Texas, Austin<br />
*[http://www.univ-nancy2.fr/pers/namer/ Namer, Fiammetta] - University of Nancy<br />
*[http://www.lr.pi.titech.ac.jp/~nanno/index.cgi?page=Tomoyuki+NANNO Nanno, Tomoyuki] - Tokyo Institute of Technology<br />
*[http://www.dlsi.ua.es/~borja/ Navarro, Borja] - University of Alicante, Spain<br />
*[http://tcc.itc.it/people/negri.html Negri, Matteo] - ITC-irst<br />
*[http://www.let.rug.nl/~nerbonne Nerbonne, John] - University of Groningen<br />
*[http://cl-www.dfki.uni-sb.de/~neumann Neumann, Guenter] - DFKI, Saarbrücken<br />
*[http://www.comp.nus.edu.sg/~nght Ng, Hwee Tou] - National University of Singapore<br />
*[http://www.hlt.utdallas.edu/~vince Ng, Vincent] - University of Texas at Dallas<br />
*[http://jdpowerwebintelligence.com/ Nicolov, Nicolas] - J.D. Power and Associates, McGraw-Hill<br />
*[http://www.slt.atr.co.jp/~night/ Nightingale, Stephen] - ATR Institute International<br />
*[http://homepages.inf.ed.ac.uk/mnissim/ Nissim, Malvina] - University of Bologna<br />
*[http://www.comp.nus.edu.sg/~niuzheng Niu, Zheng-Yu] - NU Singapore<br />
*[http://w3.msi.vxu.se/~nivre/ Nivre, Joakim] - Växjö University<br />
*[http://www.cs.berkeley.edu/~russell/norvig.html Norvig, Peter]<br />
<br />
== O ==<br />
<br />
*[http://www.ltg.ed.ac.uk/~jon/ Oberlander, Jon] - U. Edinburgh<br />
*[http://people.sabanciuniv.edu/oflazer/ Oflazer, Kemal] - Sabanci University, Istanbul, Turkey<br />
*[http://www.loa-cnr.it/oltramari.html Oltramari, Alessandro] - Laboratory for Applied Ontology, Italian National Research Council<br />
*[http://www.wlv.ac.uk/~in6093/ Orasan, Constantin] - University of Wolverhampton<br />
*[http://www.bultreebank.org/petya/OsenovaPub.html Osenova, Petya] - Bulgarian Academy of Sciences<br />
<br />
== P ==<br />
<br />
<br />
*[http://cst.dk/patrizia/ Paggio, Patrizia] - University of Copenhagen<br />
*[http://www.slt.atr.co.jp/~kpaik/ Paik, Kyonghee] - ATR Spoken Language Translation Research Laboratories<br />
*[http://www.cs.cornell.edu/People/pabo Pang, Bo] - Cornell University<br />
*[http://verbs.colorado.edu/~mpalmer/ Palmer, Martha] - University of Colorado<br />
*[http://www.isi.edu/~pantel/ Pantel, Patrick] - ISI/University of Southern California<br />
*[http://www.cs.columbia.edu/~becky/ Passonneau, Rebecca] Columbia University and Bellcore<br />
*[http://www.ilsp.gr/homepages/pastra_eng.html/ Pastra, Katerina] Institute for Language and Speech Processing<br />
*[http://www.cs.utah.edu/~sidd Patwardhan, Siddharth] - University of Utah<br />
*[http://www.l2f.inesc-id.pt/~joana/english.html Paulo Pardal] - Joana L&sup2;F] - INESC-ID<br />
*[http://perswww.kuleuven.be/yves_peirsman Peirsman, Yves] - University of Leuven<br />
*[http://www.d.umn.edu/~tpederse Pedersen, Ted] - University of Minnesota, Duluth<br />
*[http://ai-nlp.info.uniroma2.it/pennacchiotti Pennacchiotti, Marco] - University of Roma Tor Vergata<br />
*[http://www.perry.com/ Perry, John] - UCLA<br />
*[http://tcc.itc.it/people/pianesi.html Pianesi, Fabio] - ITC-irst <br />
*[http://www.resegone.com/mapb/ Piccolino Boniforti, Marco Aldo] - Rovira i Virgili University<br />
*[http://cswww.essex.ac.uk/staff/poesio Poesio, Massimo] - University of Essex<br />
*[http://www.fas.umontreal.ca/ling/olst/polguereE Polguere, Alain] - Université de Montréal<br />
*[http://fas.sfu.ca/0h/cs/people/Faculty/Popowich/popowich Popowich, Fred] - Simon Fraser University<br />
*[http://nlp.ipipan.waw.pl/~adamp/ Przepiórkowski, Adam] - Polish Academy of Sciences, Warsaw<br />
*[http://www.ling-phil.ox.ac.uk/people/staff/pulman/ Pulman, Stephen] - Oxford University<br />
*[http://www.cs.brandeis.edu/~jamesp Pustejovsky, James] - Brandeis University<br />
<br />
== Q ==<br />
<br />
== R ==<br />
<br />
*[http://www.eecs.umich.edu/~radev/ Radev, Dragomir] - University of Michigan<br />
*[http://www1.cs.columbia.edu/~rambow/ Rambow, Owen] - CCLS, Columbia University<br />
*[http://www.fask.uni-mainz.de/user/rapp Rapp, Reinhard] - Johannes Gutenberg-Universitaet Mainz<br />
*[http://www.cs.buffalo.edu/pub/WWW/faculty/rapaport/rapaport.html Rapaport, William J.] - SUNY Buffalo<br />
*[http://www.cam.sri.com/manny.html Rayner, Manny] SRI International<br />
*[http://www.cis.upenn.edu/~cliff-group/94/lrau.html Rau, Lisa]<br />
*[http://www.comp.lancs.ac.uk/computing/users/paul/ Rayson, Paul] - Lancaster University<br />
*[http://sivareddy.in Reddy, Siva] - University of York, Lexical Computing Ltd, UK<br />
*[http://www.csd.abdn.ac.uk/~ereiter Reiter, Ehud] - University of Aberdeen<br />
*[http://www.dfki.uni-sb.de/~bert Reithinger, Norbert] - Universität des Saarlandes<br />
*[http://www.reitter-it-media.de/ Reitter, David] - University of Edinburgh<br />
*[http://www.ai.mit.edu/~jrennie/ Rennie, Jason] - MIT<br />
*[http://umiacs.umd.edu/~resnik Resnik, Philip] - University of Maryland, College Park<br />
*[http://www.cs.utah.edu/~riloff/ Riloff, Ellen] - University of Utah<br />
*[http://www.cs.rochester.edu/u/ringger/ Ringger, Eric,] - University of Rochester<br />
*[http://www.di.ufpe.br/~jr Robin, Jacques, Federal] - University of Pernambuco, Brazil.<br />
*[http://www.univ-ab.pt/~vjr/ Rocio, Vitor] - Open University, Lisbon<br />
*[http://www.prodrigues.com/ Rodrigues, Paul] - Indiana University, Bloomington<br />
*[http://www.uteroemer.de/ Romer, Ute] University of Hanover<br />
*[http://www.people.cornell.edu/pages/mr249/ Rooth, Mats] - Cornell University<br />
*[http://l2r.cs.uiuc.edu Roth, Dan] - University of Illinois, Urbana-Champaign<br />
*[http://www.public.asu.edu/~droussi/ Roussinov, Dmitri] - Arizona State University<br />
*[http://www.hi.is/~eirikur/ Rögnvaldsson, Eiríkur] - University of Iceland<br />
*[http://www.uteroemer.de/ Römer, Ute] - University of Hanover<br />
*[http://people.csail.mit.edu/arum Rumshisky, Anna] - MIT<br />
*[http://rykov-cl.narod.ru/ Rykov, Vladimir]<br />
<br />
== S ==<br />
<br />
<br />
*[http://coli.uni-sb.de/~christer Samuelsson, Christer] Bell Labs<br />
*[http://ixa.si.ehu.es/Ixa/Argitalpenak/kidearen_argitalpenak?kidea=1000809006 Sarasola, Kepa] - University of the Basque Country<br />
*[http://www.cs.sfu.ca/~anoop/ Sarkar, Anoop] - currently at Simon Fraser University, formerly at University of Pennsylvania<br />
*[http://personalpages.manchester.ac.uk/staff/yutaka.sasaki/ Sasaki, Yutaka] - University of Manchester<br />
*[http://www.cog.jhu.edu/~savova/ Savova, Virginia] - MIT<br />
*[http://www.dei.unipd.it/~satta Satta, Giorgio] University of Padua<br />
*[http://www.dfki.de/~uschaefer Schaefer, Ulrich] - German Research Center for Artificial Intelligence<br />
*[http://www7.informatik.tu-muenchen.de/~scheler Scheler] - Gabriele, TU München<br />
*[http://www.ims.uni-stuttgart.de/~mike/ Schiehlen, Michael] - University of Stuttgart<br />
*[http://www.ims.uni-stuttgart.de/~schmid/ Schmid, Helmut] - University of Stuttgart<br />
*[http://www.kde.cs.uni-kassel.de/schmitz Schmitz, Christoph] - Universität Kassel<br />
*[http://www.schulteimwalde.de/ Schulte im Walde, Sabine] - Institute for Natural Language Processing, University of Stuttgart<br />
*[http://www.ics.mq.edu.au/~rolfs Schwitter, Rolf] - Macquarie University<br />
*[http://www.informatics.sussex.ac.uk/users/drs22/ Scott, Donia] - University of Sussex<br />
*[http://nlp.cs.nyu.edu/sekine Sekine, Satoshi] - New York University<br />
*[http://www.issco.unige.ch/en/staff/seretan/ Seretan, Violeta] - University of Geneva<br />
*[http://sites.google.com/site/khaledshaalan/ Shaalan, Khaled] - Cairo University<br />
*[http://www.cs.man.ac.uk/~shamsbaa/ Shams, Armin] - Metro College of Management Sciences, Manchester<br />
*[http://www.eecs.harvard.edu/~shieber/ Shieber, Stuart] - Harvard University<br />
*[http://mysite.verizon.net/sidner Sidner, Candy] - BAE Systems, AIT<br />
*[http://www.cs.rochester.edu/u/sikorski/ Sikorski, Teresa] - University of Rochester<br />
*[http://www.lingsoft.fi/~silvonen/ Silvonen, Mikko] - Lingsoft, Inc.<br />
*[http://www.bultreebank.org/kivs/ Simov, Kiril] - Bulgarian Academy of Sciences<br />
*[http://ltrc.iiit.net/anil Singh, Anil Kumar] - Language Technologies Research Centre (LTRC), International Institute of Information Technology (IIIT), Hyderabad, India<br />
*[http://www.cs.cmu.edu/~ssitaram/ Sitaram, Sunayana] - Language Technologies Institute, School of Computer Science, Carnegie Mellon University.<br />
*[http://www.utexas.edu/cola/centers/lrc/general/facultyhomes/jonathan.html Slocum, Jonathan] - The University of Texas at Austin<br />
*[http://www.cs.cmu.edu/~nasmith Smith, Noah] - Carnegie Mellon University<br />
*[http://www.cog.jhu.edu/faculty/smolensky.html Smolensky, Paul] - Johns Hopkins University<br />
*[http://www.ccl.umist.ac.uk/harold/ Somers, Harold] UMIST, Manchester<br />
*[http://www.ece.uiuc.edu/faculty/faculty.asp?rws Sproat, Richard] - University of Illinois, Urbana-Champaign<br />
*[http://www.coling.uni-freiburg.de/~staab/staab.html Staab, Steffen] - Freiburg University<br />
*[http://www.humnet.ucla.edu/humnet/linguistics/people/stabler/stabler.htm Stabler, Edward] - UCLA<br />
*[http://slt.wcl.ee.upatras.gr/stamatatos/personal.html Stamatatos, Efstathios] - University of Patras<br />
*[http://www.cs.toronto.edu/~suzanne/ Stevenson, Suzanne] - University of Toronto<br />
*[http://isl.ira.uka.de/~stiefel Stiefelhagen, Rainer] - Universität Karlsruhe<br />
*[http://www.coling.uni-freiburg.de/~strube/strube.html Strube, Michael] - University of Freiburg<br />
*[http://lvs004.googlepages.com Subramaniam, L. Venkata] - IBM India Research Lab<br />
*[http://www.csi.uottawa.ca/~szpak/ Szpakowicz, Stan] - University of Ottawa<br />
<br />
== T ==<br />
<br />
*[http://www.sfu.ca/~mtaboada Taboada, Maite] - Simon Fraser University<br />
*[http://hnk.ffzg.hr/mt/ Tadic, Marko] - Faculty of Philosophy, University of Zagreb<br />
*[http://www.ling.helsinki.fi/~tapanain Tapanainen, Pasi] - University of Helsinki<br />
*[http://www8.informatik.uni-erlangen.de/inf8/en/thabet.html Thabet, Iman] - University of Erlangen-Nuremberg<br />
*[http://www.siit.tu.ac.th/dirctory/ft_fac/thanaruk.html Theeramunkong, Thanaruk] - Sirindhorn International Institute of Technology, Thammasat University<br />
*[http://www.objs.com/thompson.htm Thompson, Craig] - Object Services and Consulting, Inc.<br />
*[http://www.let.rug.nl/~tiedeman/blog/index.php?category=1 Tiedemann, Jörg] - University of Groningen<br />
*[http://lia.univ-avignon.fr/chercheurs/torres/ Torres-Moreno, Juan-Manuel] - LIA, Université d'Avignon (France)<br />
*[http://tecfa.unige.ch/tecfa-people/traum.html Traum, David] - TECFA, Universite de Geneve<br />
*[http://www.hum.uit.no/a/trond/ Trosterud, Trond] - University of Tromsø<br />
*[http://www.racai.ro/~tufis/ Tufis, Dan] - Research Institute for Artificial Intelligence, Romanian Academy<br />
*[http://www.apperceptual.com/ Turney, Peter] - Gatineau, Canada<br />
<br />
== U ==<br />
<br />
*[http://www.coli.uni-sb.de/~hansu Uszkoreit, Hans] - University of the Saarland and DFKI Saarbrücken<br />
<br />
== V ==<br />
<br />
*[http://www.q-go.com/ van de Burgt, Stan P.] - Q-go.com<br />
*[http://www.ccl.kuleuven.be/~vincent/ccl/ Vandeghinste, Vincent] - K.U.Leuven<br />
*[http://ilk.uvt.nl/~antalb/ van den Bosch, Antal] - Tilburg University<br />
*[http://www.media.mit.edu/~nwv/ Van Dyke, Neil] - MIT Media Lab<br />
*[http://www.let.rug.nl/~vannoord/ van Noord, Gertjan] University of Groningen<br />
*[http://www.ua.es/personal/chelo.vargas Vargas, Chelo Sierra] - Universidad de Alicante<br />
*[http://grid.let.rug.nl/~mettina/ Veenstra, Mettina] University of Groningen<br />
*[http://www.cs.brandeis.edu/~marc/home.html Verhagen, Marc] - Brandeis University<br />
*[http://www.up.univ-mrs.fr/veronis/ Véronis, Jean] - Université de Provence<br />
*[http://www.dlsi.ua.es/~vicedo/vicedo_en.html Vicedo, Jose Luis] - Alicante University<br />
*[http://www.inf.unisinos.br/~renata/ Vieira, Renata] - Universidade do Vale do Rio dos Sinos, Brazil<br />
*[http://www.cl.cam.ac.uk/~av208/ Villavicencio, Aline] - Federal University of Rio Grande do Sul, Brazil<br />
*[http://home.planet.nl/~weiss075/ Vossen, Piek] Irion Technologies<br />
*[http://www.ling.helsinki.fi/~avoutila/ Voutilainen, Atro] - University of Helsinki<br />
<br />
== W ==<br />
<br />
*[http://www.dfki.de/~wahlster/ Wahlster, Wolfgang] - Universität des Saarlandes<br />
*[http://www.uindy.gr/faculty/cv/wallace_manolis/ Wallace, Manolis] - National Technical University of Athens<br />
*[http://www.cs.cmu.edu/~yww/ Wang, William Yang] - Carnegie Mellon University<br />
*[http://www.nigelward.com/ Ward, Nigel]<br />
*[http://www.ribbitsoft.com/research/watson/index.html Watson, Bruce] Ribbit Soft.<br />
*[http://hiplab.newcastle.edu.au/~pwatters Watters, Paul A. ] U. of Newcastle, Australia<br />
*[http://www.nick-webb.net Webb, Nick] - SUNY Albany<br />
*[http://www.pages.drexel.edu/~rw37/ Weber, Rosina] - Drexel University<br />
*[http://www.ucsc.cmb.ac.lk/People/rw Weerasinghe, Ruvan] - University of Colombo School of Computing<br />
*[http://www.latl.unige.ch/personal/eric_f.html Wehrli, Eric] - University of Geneva<br />
*[http://www.cs.tu-berlin.de/~ww/ Weisweber, Wilhelm] - Technical University of Berlin<br />
*[http://www.ukp.tu-darmstadt.de Weimer, Markus] - University of Technology Darmstadt<br />
*[http://www.cis.upenn.edu/~bonnie Webber, Bonnie Lynn] - University of Pennsylvania<br />
*[http://www.dcs.shef.ac.uk/~yorick Wilks, Yorick] - University of Sheffield<br />
*[http://cs.haifa.ac.il/~shuly Wintner, Shuly] - University of Haifa, Israel<br />
*[http://www.se.cuhk.edu.hk/~kfwong/ Wong, Kam-Fai] - Chinese University of Hong Kong<br />
*[http://explorer.csse.uwa.edu.au/resume Wong, Wilson] - University of Western Australia<br />
*[http://www.cs.utexas.edu/users/ywwong/ Wong, Yuk Wah] - University of Texas at Austin<br />
*[http://www.cs.man.ac.uk/~wroec/ Wroe, Chris] - University of Manchester<br />
*[http://www.cs.ust.hk/faculty/dekai/bio.html Wu, Dekai] - HKUST<br />
<br />
== X ==<br />
*[http://faculty.washington.edu/fxia/ Xia, Fei] - University of Washington<br />
*[http://www1.i2r.a-star.edu.sg/~dyxiong/ Xiong, Deyi] - Institute for Infocomm Research, Singapore<br />
<br />
== Y ==<br />
<br />
*[http://www.cs.helsinki.fi/u/yangarbe/ Yangarber, Roman] - University of Helsinki<br />
*[http://www.cis.upenn.edu/~cliff-group/94/yarowsky.html Yarowsky, David] - University of Pennsylvania<br />
*[http://www.icl.pku.edu.cn/member/yusw/ Yu, Shiwen] - Peking University<br />
*[http://www.denizyuret.com/ Yuret, Deniz] - Koç University<br />
<br />
== Z ==<br />
<br />
*[http://ufal.mff.cuni.cz/~zabokrtsky Žabokrtský, Zdeněk] - Charles University in Prague<br />
*[http://ai-nlp.info.uniroma2.it/zanzotto Zanzotto, Fabio Massimo] - University of Roma Tor Vergata<br />
*[http://corpling.uis.georgetown.edu/amir Zeldes, Amir] - Georgetown University<br />
*[http://ufal.mff.cuni.cz/~zeman/ Zeman, Dan] - Univerzita Karlova v&nbsp;Praze<br />
*[http://www.ukp.tu-darmstadt.de/ Zesch, Torsten] - Darmstadt University of Technology<br />
*[http://www1.i2r.a-star.edu.sg/~mzhang/ Zhang, Min] - Institute for Infocomm Research, Singapore<br />
*[http://bcmi.sjtu.edu.cn/~zhaohai/ Zhao, Hai] - City University of Hong Kong<br />
*[http://pages.cs.wisc.edu/~jerryzhu/ Zhu, Xiaojin (Jerry)] - University of Wisconsin, Madison<br />
*[http://www.csse.monash.edu.au/~ingrid/ Zukerman, Ingrid] - Monash University</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Newsgroups,_mailing_lists&diff=12149Newsgroups, mailing lists2018-01-21T21:53:25Z<p>Tristan Miller: Update MT List link</p>
<hr />
<div><!-- Please keep this list in alphabetical order --><br />
* [http://www.cs.um.edu.mt/mailman/listinfo/sigsemitic ACL SIG on Computational Approaches to Semitic Languages]<br />
* [https://groups.google.com/a/datacommunitydc.org/forum/#!forum/nlp Data Community DC Natural Language Processing]<br />
* [http://www.meetup.com/DC-NLP/messages/archive/ DC NLP Meetup Group mailing list]<br />
* [http://tech.groups.yahoo.com/group/CAN-TAL-NLP/ CAN-TAL-NLP] - Canadian NLP<br />
* [news:comp.ai.nat-lang comp.ai.nat-lang] newsgroup<br />
* [http://torvald.aksis.uib.no/corpora/ Corpora List]<br />
* [http://sgi.nu/enron/mailinglist.php Enron Email Corpus Mailing List]<br />
* [https://cs.haifa.ac.il/mailman/listinfo/formalgrammar FG Mailing List] - Formal Grammar<br />
* [http://ling.ohio-state.edu/HPSG/Majordomo.html HPSG Mailing List] - Head-Driven Phrase Structure Grammar<br />
* [http://heim.ifi.uio.no/~dag/ling-tex.html Ling-TeX] - Typesetting linguistics material with TeX/LaTeX<br />
* [http://linguistlist.org/lists/index.html LINGUIST List]<br />
* [http://www.eamt.org/mt-list.php MT List] - Machine Translation<br />
* [http://mallet.cs.umass.edu/mailinglist.php MALLET software mailing list]<br />
* [http://listserv.linguistlist.org/archives/nsm-l.html Natural Semantic Metalanguage List]<br />
* [http://groups.google.com/group/nltk-users NLTK software mailing list]<br />
* [http://tech.groups.yahoo.com/group/Pashto-Urdu-Computational-Linguistics/ Pashto-Urdu] - Pashto-Urdu Computational Linguistics<br />
* [http://listserv.hum.gu.se/mailman/listinfo/senseval-discuss SENSEVAL discussion list] - word sense disambiguation<br />
* [http://tech.groups.yahoo.com/group/SentimentAI/ SentimentAI] - sentiment, opinions, and affect in text<br />
* [http://www.sigsem.org/wiki/Mailing_list SIGSEM] - mailing list on computational semantics<br />
* [http://www.siggen.org/mailing.html SIGGEN] - mailing list on natural language generation<br />
* [http://www.sigir.org/sigirlist/issues/ SIG-IRList Archives] - Information Retrieval<br />
* [https://mailman.stanford.edu/mailman/listinfo/java-nlp-user Stanford NLP software mailing list]<br />
* [http://tech.groups.yahoo.com/group/syntax/ Syntax] - linguistics, language, syntax, semantics, generative grammar, generative linguistics, formal grammar, minimalism<br />
* [http://tech.groups.yahoo.com/group/TextAnalytics/ Text Analytics]<br />
<br />
==Other lists of newsgroups and mailing lists==<br />
* [http://www.cs.technion.ac.il/~gabr/resources/news_mail.html Newsgroups and mailing lists for Text, Speech and Language Processing]<br />
<br />
==IRC channels==<br />
* #linguistics on irc.freenode.net (general and computational linguistics)<br />
* #nlp on irc.freenode.net (computational linguistics)<br />
<br />
==See also==<br />
* [[List of resources by language]]<br />
* [[Special interest groups]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12033Employment opportunities, postdoctoral positions, summer jobs2017-11-03T10:38:36Z<p>Tristan Miller: Independent Research Group Leader, Department of Computer Science, TU Darmstadt</p>
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<br />
== Independent Research Group Leader, Department of Computer Science, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Department of Computer Science], Technische Universität Darmstadt, Germany<br />
* Title: AIndependent Research Group Leader<br />
* Specialty: Natural Language Processing for the Humanities<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]<br />
<br />
Independent Research Group Leader "Natural Language Processing for the <br />
Humanities", Technische Universität Darmstadt<br />
<br />
The Department of Computer Science of Technische Universität Darmstadt <br />
seeks to fill an Independent Research Group (IRG) Leader position for <br />
the initial duration of four years. The program allows young <br />
scientists to found their own research group. It is similar in spirit <br />
to DFG's Emmy Noether Program. The focus of the Independent Research <br />
Group will be on cutting-edge Natural Language Processing research <br />
with its novel applications to support humanities research, e.g. <br />
mining scientific literature, automatic discourse analysis, or <br />
multimodal content classification to identify bias or tone <br />
computationally. The goal of the position is to strengthen the rapidly <br />
growing profile of the Department in Data Analytics at the <br />
intersection of Natural Language Processing, Computer Vision, and <br />
Machine Learning on the one side, and to further develop the connection <br />
between Computer Science and the Humanities on the other side.<br />
<br />
The IRG Leader will receive an opportunity to conduct independent <br />
research and teaching, and the funding to hire a PhD student (similar <br />
to assistant professors). Candidates must have completed their PhD in <br />
Computer Science or related area, have an outstanding publication <br />
record and demonstrate experience in working with the international <br />
research community. Ideally they have held at least one postdoc <br />
position at a university other than the one they obtained their PhD <br />
degree from. The program offers competitive personal compensation and <br />
access to resources. The IRG Leaders are employed by TU Darmstadt on <br />
its own pay scale TV-TU Darmstadt. Applicants are selected based on <br />
their credentials, references, and participation in a scientific <br />
colloquium. We expect the ability to work independently, personal <br />
commitment, team and communication abilities, as well as the <br />
willingness to cooperate in a multi-disciplinary team. We specifically <br />
invite applications of women. Among those equally qualified, <br />
handicapped applicants will receive preferential consideration. <br />
International applications are particularly encouraged.<br />
<br />
The successful candidate will be given the opportunity to join the PI <br />
team of the graduate school [https://www.aiphes.tu-darmstadt.de/ "Adaptive Preparation of Information from Heterogeneous Sources" (AIPHES)]. The project conducts innovative <br />
research in a cross-disciplinary context. To that end, methods in <br />
computational linguistics, natural language processing, machine <br />
learning, network analysis, and automated quality assessment are <br />
developed. AIPHES investigates a novel scenario for information <br />
preparation from heterogeneous sources, within the application context <br />
of multi-document summarization. There is close interaction with end <br />
users who prepare textual documents in an online editorial office, and <br />
who should therefore benefit from the results of AIPHES. In-depth <br />
knowledge in one of the above areas is required. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked <br />
among the top ones in respective rankings of German universities. Its <br />
unique [https://www.cedifor.de/en/ "Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences" (CEDIFOR)] emphasizes natural language processing, text mining, machine learning, as well as <br />
scalable infrastructures for assessment and aggregation of knowledge <br />
applied to novel research problems from the Humanities domain. <br />
<br />
Applications should be submitted to <br />
https://public.ukp.informatik.tu-darmstadt.de/irgrecruitment/ by <br />
November 24, 2017 and include a research and teaching statement along <br />
with the CV, publication list, name of three academic references, and <br />
further supporting documents. In case of questions, please contact <br />
Prof. Dr. Iryna Gurevych: [mailto:gurevych@ukp.informatik.tu-darmstadt.de gurevych@ukp.informatik.tu-darmstadt.de]. The position is open until filled.<br />
<br />
== PostDoc / Senior Researcher, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: PostDoc / Senior Researcher<br />
* Specialty: NLP applications to humanities, social and educational sciences; multimodal analysis and large-scale knowledge extraction<br />
* Location: Darmstadt<br />
* Deadline: November 25, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
PostDoc / Senior Researcher<br />
(for an initial term of two years with an option for an extension)<br />
<br />
to strengthen the group’s expertise in the area of Natural Language Processing with its novel applications to Humanities, Social and Educational Sciences with a focus on multimodal analysis and large-scale knowledge extraction. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP). The group has a strong research profile in computational linguistics, machine learning and text mining. Core research areas include semantic text analysis and resources with their applications in multimodal information processing, knowledge discovery, and discourse analysis. The lab closely cooperates with groups in machine learning, image analysis, and interactive data analytics of the Computer Science department and a large number of research labs worldwide. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization/PhD in Natural Language Processing or Text Mining, preferably with expertise in research and development projects and strong communication skills in English and German (optional). The successful applicant will work on research and development activities within the profile area described above and – based on the previous experience and qualification – will be given an opportunity to contribute to teaching courses, PhD student co-supervision, and project management activities.<br />
<br />
Ideally, the candidates should have demonstrable experience in NLP research, designing and implementing complex (NLP and/or ML) systems, applying Machine Learning incl. neural networks to text processing (e.g. document classification, sequence classification, clustering, etc.), information retrieval and databases, scalable data processing, and strong programming skills in Python and/or Java. <br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by November 25, 2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: interactive text analysis, natural language processing infrastructure<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Text <br />
Analysis and Natural Language Processing Infrastructure. The UKP Lab <br />
is a research group comprising over 30 team members who work on <br />
various aspects of Natural Language Processing (NLP) with a rapidly <br />
developing focus on Interactive Machine Learning, and who provide a <br />
wide range of open source software packages for interactive and <br />
automatic text analysis to research and industry communities.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Natural Language Processing or Text Mining, <br />
preferably with expertise in research and development projects and <br />
strong communication skills in English and German. The successful <br />
applicant will work on research and development activities regarding <br />
text annotation by end-users (researchers, analysts, etc.), <br />
information recommendation, information retrieval, or semantic text <br />
analysis, and to create the corresponding applications and software <br />
components in coordination with the prospective end-users. <br />
<br />
Ideally, the candidates should have demonstrable experience in <br />
designing and implementing complex (NLP and/or ML) systems (frontend <br />
and backend), in applying NLP-related Machine Learning-based methods <br />
(e.g. document classification, sequence classification, clustering, <br />
etc.), experience with information retrieval systems and databases, <br />
scalable data processing, and strong programming skills especially in <br />
Java. Experience with neural network architectures and demonstrable <br />
engagement in open source projects are strong pluses.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Data Analytics” and the Research Training Group “Adaptive <br />
Information Processing of Heterogeneous Content” (AIPHES) funded by <br />
the DFG emphasize NLP, machine learning, text mining and scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members working on common <br />
goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please submit your application via the following form by November 24, <br />
2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The <br />
position is open until filled.<br />
<br />
== KU Leuven, Belgium : Researcher in Automated Reading of Documents ==<br />
<br />
* KU Leuven, Belgium: Postdoc or junior researcher in Automated Reading of Documents <br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral or research fellow<br />
* Specialty: Machine Learning and Natural Language Processing<br />
* Location: Leuven, Belgium<br />
* Deadline: Ongoing, desired start date: as soon as possible <br />
* Date posted: November 1, 2017<br />
* Contact: [mailto:sien.moens@cs.kuleuven.be Prof. Marie-Francine Moens]<br />
<br />
'''Researcher in Automated Reading of Documents''' <br/><br />
(Department of Computer Science, KU Leuven, Belgium)<br />
<br />
The Language Intelligence & Information Retrieval lab (https://liir.cs.kuleuven.be) that is part of the Human Computer Interaction group of the Department of Computer Science of KU Leuven in Belgium has an open position for a motivated researcher interested in the latest developments in artificial intelligence for the automated reading of documents. <br />
<br />
The research is carried out in the frame of the SaaS project (Self-learning SaaS platform for simplification of data-intensive customer experiences). The goal is to design, develop and test novel machine learning models that are self-learning and that can be applied for real-time processing of unstructured or semi-structured documents. Special attention will go to deep learning models relying on character-based or word-based representations of content. <br />
<br />
We offer a research position in a research team that has an outstanding international reputation in natural language processing and understanding, multimedia mining, machine learning and information retrieval. Within the team we study both theoretical modelling and challenging applications. We investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. We have a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, user generated content mining, and web mining and search. KU Leuven is located about 25 kilometers from Brussels, the capital of Europe. For the second year in a row, KU Leuven leads the Reuters ranking as Europe’s most innovative university. <br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field.<br />
* Research experience in machine learning.<br />
<br />
'''Desired'''<br />
* Good knowledge of the English language and some knowledge of French or Dutch.<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds.<br />
* Desired start date: as soon as possible.<br />
* Competitive salary. <br />
<br />
'''How to Apply''' <br/><br />
If interested, send your CV and motivation letter to Prof. Marie-Francine Moens (sien.moens@cs.kuleuven.be). The position will be filled in as soon as possible.<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Spring/Summer 2018<br />
* Date posted: October 31, 2017<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting Spring or Summer 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is Spring 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder''' <br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
== Two Postdoctoral Positions on Interpretable Vector Space Models ==<br />
*Employer: Cardiff University<br />
*Title: Postdoctoral research associate<br />
*Speciality: Neural networks, statistical relational learning, natural language processing<br />
*Location: Cardiff, UK<br />
*Deadline: November 2 2017<br />
*Date posted: October 6, 2017<br />
*Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC). The overall aims of this project are (i) to learn interpretable vector space representations of entities and their relationships, and (ii) to exploit these vector space representations for various forms of flexible reasoning with, and learning from structured data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
The aim of these positions will be to contribute to one or more of the following topics.<br />
<br />
1) Learning structured event embeddings. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with cognitively inspired representations (e.g. based on the theory of conceptual spaces). Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. <br />
<br />
2) Combining statistical relational learning with vector space models of commonsense reasoning. Low-dimensional vector space representations can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning (SRL) can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths, enabling interpretable and robust plausible reasoning from sparse relational data.<br />
<br />
3) Geometric representations of logical theories. Most vector space models for knowledge base completion simply represent entities, attributes and relations as vectors. In many domains, however, plausible inferences rely on complex dependencies that cannot be captured by such representations. As an alternative, we will develop methods in which predicates are represented as regions, and logical formulas correspond to qualitative constraints on the spatial configurations of these regions. This model will support more complex inferences than existing approaches, will allow us to exploit existing domain knowledge when learning vector space representations, and will conversely allow us derive approximate logical theories from a learned embedding.<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Salaried 4-year PhD Position in Computational Linguistics/NLP at Stockholm University ==<br />
*Employer: Stockholm University, Sweden<br />
*Title: PhD candidate<br />
*Speciality: Computational Linguistics/Natural Language Processing<br />
*Location: Stockholm, Sweden<br />
*Deadline: October 16, 2017<br />
*Date posted: September 20, 2017<br />
*Contact: [mailto:robert@ling.su.se Robert Östling]<br />
<br />
More information and application form: http://www.su.se/english/about/working-at-su/jobs?rmlang=UK&rmpage=job&rmjob=3869<br />
<br />
The Department of Linguistics at Stockholm University is looking for a new PhD candidate in the area of computational linguistics/natural language processing. PhD candidates are regular employees of Stockholm University, with a starting salary of 25,300 SEK (2,650 EUR; 3,200 USD) per month and the same benefits and social security as other University employees. The position is fully funded for 4 years. Extension up to one year is possible if the candidate performs teaching or other duties at the department, and further extension is granted in case of parental or sick leave.<br />
<br />
The choice of thesis topic is not restricted to a particular project, but should be aligned with the research profile of the department. Possible topics include multilingual NLP methods, machine translation, or computational methods for other areas of research at the department (language acquisition, linguistic typology, phonetics, sign language).<br />
<br />
Potential applicants are encouraged to contact [mailto:robert@ling.su.se Robert Östling] to discuss possible thesis projects, or other issues related to the position.<br />
<br />
== Tenure Line Assistant Professor Position in Linguistics at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Tenure Line Assistant Professor Position in Linguistics at Northwestern University<br />
*Speciality: Meaning<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2017<br />
*Date posted: September 18, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
http://www.linguistics.northwestern.edu/about/news/faculty-search.html<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line assistant professor position with a start date of September 1, 2018. We are looking for candidates with research and teaching interests in meaning, broadly construed. We are particularly interested in candidates whose research program includes cognitive, computational, and/or social approaches. The successful candidate will join a vibrant interdisciplinary community of researchers in the science of language, including computer science, philosophy, psychology, cognitive neuroscience, and speech science.<br />
<br />
To receive fullest consideration, applications should be uploaded by December 1, 2017. Candidates must hold a Ph.D. in Linguistics, Cognitive Science, Computer Science, Psychology, or a related field by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work, teaching evaluations (if available), and the names of three references (with their contact information). References will separately receive upload instructions after you have submitted your application (letters of reference should arrive as close as December 1st as possible).<br />
<br />
The Department is strongly committed to enhancing diversity, equity and inclusion in all aspects – including, but not limited to, race/ethnicity, and gender, as well as disability, sexual orientation, and gender expression and identity. We encourage applications from candidates that share this vision.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair.<br />
<br />
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12032Employment opportunities, postdoctoral positions, summer jobs2017-11-03T10:38:14Z<p>Tristan Miller: PostDoc / Senior Researcher, UKP Lab, TU Darmstadt</p>
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== PostDoc / Senior Researcher, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: PostDoc / Senior Researcher<br />
* Specialty: NLP applications to humanities, social and educational sciences; multimodal analysis and large-scale knowledge extraction<br />
* Location: Darmstadt<br />
* Deadline: November 25, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
PostDoc / Senior Researcher<br />
(for an initial term of two years with an option for an extension)<br />
<br />
to strengthen the group’s expertise in the area of Natural Language Processing with its novel applications to Humanities, Social and Educational Sciences with a focus on multimodal analysis and large-scale knowledge extraction. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP). The group has a strong research profile in computational linguistics, machine learning and text mining. Core research areas include semantic text analysis and resources with their applications in multimodal information processing, knowledge discovery, and discourse analysis. The lab closely cooperates with groups in machine learning, image analysis, and interactive data analytics of the Computer Science department and a large number of research labs worldwide. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization/PhD in Natural Language Processing or Text Mining, preferably with expertise in research and development projects and strong communication skills in English and German (optional). The successful applicant will work on research and development activities within the profile area described above and – based on the previous experience and qualification – will be given an opportunity to contribute to teaching courses, PhD student co-supervision, and project management activities.<br />
<br />
Ideally, the candidates should have demonstrable experience in NLP research, designing and implementing complex (NLP and/or ML) systems, applying Machine Learning incl. neural networks to text processing (e.g. document classification, sequence classification, clustering, etc.), information retrieval and databases, scalable data processing, and strong programming skills in Python and/or Java. <br />
<br />
The research environment is excellent. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones among the German universities. Its unique Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) and the Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasize NLP, machine learning and text mining. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest standards, cooperative work style and close interaction of team members.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience and the names of three referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please submit your application via the following form by November 25, 2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: interactive text analysis, natural language processing infrastructure<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Text <br />
Analysis and Natural Language Processing Infrastructure. The UKP Lab <br />
is a research group comprising over 30 team members who work on <br />
various aspects of Natural Language Processing (NLP) with a rapidly <br />
developing focus on Interactive Machine Learning, and who provide a <br />
wide range of open source software packages for interactive and <br />
automatic text analysis to research and industry communities.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Natural Language Processing or Text Mining, <br />
preferably with expertise in research and development projects and <br />
strong communication skills in English and German. The successful <br />
applicant will work on research and development activities regarding <br />
text annotation by end-users (researchers, analysts, etc.), <br />
information recommendation, information retrieval, or semantic text <br />
analysis, and to create the corresponding applications and software <br />
components in coordination with the prospective end-users. <br />
<br />
Ideally, the candidates should have demonstrable experience in <br />
designing and implementing complex (NLP and/or ML) systems (frontend <br />
and backend), in applying NLP-related Machine Learning-based methods <br />
(e.g. document classification, sequence classification, clustering, <br />
etc.), experience with information retrieval systems and databases, <br />
scalable data processing, and strong programming skills especially in <br />
Java. Experience with neural network architectures and demonstrable <br />
engagement in open source projects are strong pluses.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Data Analytics” and the Research Training Group “Adaptive <br />
Information Processing of Heterogeneous Content” (AIPHES) funded by <br />
the DFG emphasize NLP, machine learning, text mining and scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members working on common <br />
goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please submit your application via the following form by November 24, <br />
2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The <br />
position is open until filled.<br />
<br />
== KU Leuven, Belgium : Researcher in Automated Reading of Documents ==<br />
<br />
* KU Leuven, Belgium: Postdoc or junior researcher in Automated Reading of Documents <br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral or research fellow<br />
* Specialty: Machine Learning and Natural Language Processing<br />
* Location: Leuven, Belgium<br />
* Deadline: Ongoing, desired start date: as soon as possible <br />
* Date posted: November 1, 2017<br />
* Contact: [mailto:sien.moens@cs.kuleuven.be Prof. Marie-Francine Moens]<br />
<br />
'''Researcher in Automated Reading of Documents''' <br/><br />
(Department of Computer Science, KU Leuven, Belgium)<br />
<br />
The Language Intelligence & Information Retrieval lab (https://liir.cs.kuleuven.be) that is part of the Human Computer Interaction group of the Department of Computer Science of KU Leuven in Belgium has an open position for a motivated researcher interested in the latest developments in artificial intelligence for the automated reading of documents. <br />
<br />
The research is carried out in the frame of the SaaS project (Self-learning SaaS platform for simplification of data-intensive customer experiences). The goal is to design, develop and test novel machine learning models that are self-learning and that can be applied for real-time processing of unstructured or semi-structured documents. Special attention will go to deep learning models relying on character-based or word-based representations of content. <br />
<br />
We offer a research position in a research team that has an outstanding international reputation in natural language processing and understanding, multimedia mining, machine learning and information retrieval. Within the team we study both theoretical modelling and challenging applications. We investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. We have a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, user generated content mining, and web mining and search. KU Leuven is located about 25 kilometers from Brussels, the capital of Europe. For the second year in a row, KU Leuven leads the Reuters ranking as Europe’s most innovative university. <br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field.<br />
* Research experience in machine learning.<br />
<br />
'''Desired'''<br />
* Good knowledge of the English language and some knowledge of French or Dutch.<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds.<br />
* Desired start date: as soon as possible.<br />
* Competitive salary. <br />
<br />
'''How to Apply''' <br/><br />
If interested, send your CV and motivation letter to Prof. Marie-Francine Moens (sien.moens@cs.kuleuven.be). The position will be filled in as soon as possible.<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Spring/Summer 2018<br />
* Date posted: October 31, 2017<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting Spring or Summer 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is Spring 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder''' <br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
== Two Postdoctoral Positions on Interpretable Vector Space Models ==<br />
*Employer: Cardiff University<br />
*Title: Postdoctoral research associate<br />
*Speciality: Neural networks, statistical relational learning, natural language processing<br />
*Location: Cardiff, UK<br />
*Deadline: November 2 2017<br />
*Date posted: October 6, 2017<br />
*Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC). The overall aims of this project are (i) to learn interpretable vector space representations of entities and their relationships, and (ii) to exploit these vector space representations for various forms of flexible reasoning with, and learning from structured data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
The aim of these positions will be to contribute to one or more of the following topics.<br />
<br />
1) Learning structured event embeddings. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with cognitively inspired representations (e.g. based on the theory of conceptual spaces). Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. <br />
<br />
2) Combining statistical relational learning with vector space models of commonsense reasoning. Low-dimensional vector space representations can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning (SRL) can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths, enabling interpretable and robust plausible reasoning from sparse relational data.<br />
<br />
3) Geometric representations of logical theories. Most vector space models for knowledge base completion simply represent entities, attributes and relations as vectors. In many domains, however, plausible inferences rely on complex dependencies that cannot be captured by such representations. As an alternative, we will develop methods in which predicates are represented as regions, and logical formulas correspond to qualitative constraints on the spatial configurations of these regions. This model will support more complex inferences than existing approaches, will allow us to exploit existing domain knowledge when learning vector space representations, and will conversely allow us derive approximate logical theories from a learned embedding.<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Salaried 4-year PhD Position in Computational Linguistics/NLP at Stockholm University ==<br />
*Employer: Stockholm University, Sweden<br />
*Title: PhD candidate<br />
*Speciality: Computational Linguistics/Natural Language Processing<br />
*Location: Stockholm, Sweden<br />
*Deadline: October 16, 2017<br />
*Date posted: September 20, 2017<br />
*Contact: [mailto:robert@ling.su.se Robert Östling]<br />
<br />
More information and application form: http://www.su.se/english/about/working-at-su/jobs?rmlang=UK&rmpage=job&rmjob=3869<br />
<br />
The Department of Linguistics at Stockholm University is looking for a new PhD candidate in the area of computational linguistics/natural language processing. PhD candidates are regular employees of Stockholm University, with a starting salary of 25,300 SEK (2,650 EUR; 3,200 USD) per month and the same benefits and social security as other University employees. The position is fully funded for 4 years. Extension up to one year is possible if the candidate performs teaching or other duties at the department, and further extension is granted in case of parental or sick leave.<br />
<br />
The choice of thesis topic is not restricted to a particular project, but should be aligned with the research profile of the department. Possible topics include multilingual NLP methods, machine translation, or computational methods for other areas of research at the department (language acquisition, linguistic typology, phonetics, sign language).<br />
<br />
Potential applicants are encouraged to contact [mailto:robert@ling.su.se Robert Östling] to discuss possible thesis projects, or other issues related to the position.<br />
<br />
== Tenure Line Assistant Professor Position in Linguistics at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Tenure Line Assistant Professor Position in Linguistics at Northwestern University<br />
*Speciality: Meaning<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2017<br />
*Date posted: September 18, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
http://www.linguistics.northwestern.edu/about/news/faculty-search.html<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line assistant professor position with a start date of September 1, 2018. We are looking for candidates with research and teaching interests in meaning, broadly construed. We are particularly interested in candidates whose research program includes cognitive, computational, and/or social approaches. The successful candidate will join a vibrant interdisciplinary community of researchers in the science of language, including computer science, philosophy, psychology, cognitive neuroscience, and speech science.<br />
<br />
To receive fullest consideration, applications should be uploaded by December 1, 2017. Candidates must hold a Ph.D. in Linguistics, Cognitive Science, Computer Science, Psychology, or a related field by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work, teaching evaluations (if available), and the names of three references (with their contact information). References will separately receive upload instructions after you have submitted your application (letters of reference should arrive as close as December 1st as possible).<br />
<br />
The Department is strongly committed to enhancing diversity, equity and inclusion in all aspects – including, but not limited to, race/ethnicity, and gender, as well as disability, sexual orientation, and gender expression and identity. We encourage applications from candidates that share this vision.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair.<br />
<br />
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=12031Employment opportunities, postdoctoral positions, summer jobs2017-11-03T10:37:48Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
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== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: interactive text analysis, natural language processing infrastructure<br />
* Location: Darmstadt<br />
* Deadline: November 24, 2017<br />
* Date posted: November 3, 2017<br />
* Contact: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of <br />
Computer Science, Technische Universität (TU) Darmstadt, Germany has <br />
an opening for an<br />
<br />
'''Associate Research Scientist'''<br><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Text <br />
Analysis and Natural Language Processing Infrastructure. The UKP Lab <br />
is a research group comprising over 30 team members who work on <br />
various aspects of Natural Language Processing (NLP) with a rapidly <br />
developing focus on Interactive Machine Learning, and who provide a <br />
wide range of open source software packages for interactive and <br />
automatic text analysis to research and industry communities.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Natural Language Processing or Text Mining, <br />
preferably with expertise in research and development projects and <br />
strong communication skills in English and German. The successful <br />
applicant will work on research and development activities regarding <br />
text annotation by end-users (researchers, analysts, etc.), <br />
information recommendation, information retrieval, or semantic text <br />
analysis, and to create the corresponding applications and software <br />
components in coordination with the prospective end-users. <br />
<br />
Ideally, the candidates should have demonstrable experience in <br />
designing and implementing complex (NLP and/or ML) systems (frontend <br />
and backend), in applying NLP-related Machine Learning-based methods <br />
(e.g. document classification, sequence classification, clustering, <br />
etc.), experience with information retrieval systems and databases, <br />
scalable data processing, and strong programming skills especially in <br />
Java. Experience with neural network architectures and demonstrable <br />
engagement in open source projects are strong pluses.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Data Analytics” and the Research Training Group “Adaptive <br />
Information Processing of Heterogeneous Content” (AIPHES) funded by <br />
the DFG emphasize NLP, machine learning, text mining and scalable <br />
infrastructures for the assessment and aggregation of knowledge. UKP <br />
Lab is a highly dynamic research group committed to high-quality <br />
research results, technologies of the highest standards, cooperative <br />
work style and close interaction of team members working on common <br />
goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please submit your application via the following form by November 24, <br />
2017: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The <br />
position is open until filled.<br />
<br />
== KU Leuven, Belgium : Researcher in Automated Reading of Documents ==<br />
<br />
* KU Leuven, Belgium: Postdoc or junior researcher in Automated Reading of Documents <br />
* Employer: KU Leuven, Belgium<br />
* Title: Postdoctoral or research fellow<br />
* Specialty: Machine Learning and Natural Language Processing<br />
* Location: Leuven, Belgium<br />
* Deadline: Ongoing, desired start date: as soon as possible <br />
* Date posted: November 1, 2017<br />
* Contact: [mailto:sien.moens@cs.kuleuven.be Prof. Marie-Francine Moens]<br />
<br />
'''Researcher in Automated Reading of Documents''' <br/><br />
(Department of Computer Science, KU Leuven, Belgium)<br />
<br />
The Language Intelligence & Information Retrieval lab (https://liir.cs.kuleuven.be) that is part of the Human Computer Interaction group of the Department of Computer Science of KU Leuven in Belgium has an open position for a motivated researcher interested in the latest developments in artificial intelligence for the automated reading of documents. <br />
<br />
The research is carried out in the frame of the SaaS project (Self-learning SaaS platform for simplification of data-intensive customer experiences). The goal is to design, develop and test novel machine learning models that are self-learning and that can be applied for real-time processing of unstructured or semi-structured documents. Special attention will go to deep learning models relying on character-based or word-based representations of content. <br />
<br />
We offer a research position in a research team that has an outstanding international reputation in natural language processing and understanding, multimedia mining, machine learning and information retrieval. Within the team we study both theoretical modelling and challenging applications. We investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. We have a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, user generated content mining, and web mining and search. KU Leuven is located about 25 kilometers from Brussels, the capital of Europe. For the second year in a row, KU Leuven leads the Reuters ranking as Europe’s most innovative university. <br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field.<br />
* Research experience in machine learning.<br />
<br />
'''Desired'''<br />
* Good knowledge of the English language and some knowledge of French or Dutch.<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds.<br />
* Desired start date: as soon as possible.<br />
* Competitive salary. <br />
<br />
'''How to Apply''' <br/><br />
If interested, send your CV and motivation letter to Prof. Marie-Francine Moens (sien.moens@cs.kuleuven.be). The position will be filled in as soon as possible.<br />
<br />
== CU Boulder: Postdoc in Machine Learning with an Emphasis on Speech and Language Processing ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Associate<br />
* Specialty: Machine Learning, Speech and Language Processing<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Spring/Summer 2018<br />
* Date posted: October 31, 2017<br />
* Contact: [mailto:sidney.dmello@colorado.edu Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning with an Emphasis on Speech and Language Processing''' <br/><br />
(Department of Computer Science and Institute of Cognitive Science at the University of Colorado Boulder)<br />
<br />
The Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral research associate starting Spring or Summer 2018 for one year and renewable for a second (and third) year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to speech and language processing to solve challenging, but impactful, real-world problems. He/she will participate in the development and application of advanced machine learning techniques (e.g., deep recurrent neural networks) to multi-party speech data collected in authentic contexts (e.g., classroom discourse, small group collaborative problem solving). <br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science and the Institute of Cognitive Science. <br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop new technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire<br />
* Research experience in advanced machine learning (e.g., deep learning, probabilistic graphical models)<br />
* Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas: acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling<br />
<br />
'''Job Details'''<br />
* One year initial position with possible extension to a second and third year based on performance and availability of funds<br />
* Desired start date is Spring 2018. However, start date is negotiable<br />
* Competitive salary with benefits commensurate with qualifications<br />
<br />
'''How to Apply''' <br/><br />
Please complete the following form: https://tinyurl.com/CUPostDoc1 and upload the following required documents: (1) cover letter, (2) current CV, and (3) one or two representative publications '''as a single PDF''' document named '''FirstNameLastName.pdf'''.<br />
<br />
Additional documents will be required from candidates selected for further review after the initial documents are received: (4) – The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and (5) – List of references<br />
<br />
'''About the University of Colorado and the City of Boulder''' <br/><br />
The University of Colorado Boulder is a widely recognized and respected research university in the U.S. Its 11 research institutes house more than 900 researchers, students, and staff, making a major contribution to the research infrastructure of the university and local economy. Boulder is one of the 34 public research institutions belonging to the Association of American Universities (AAU). It contributes to the local community via research partnerships, education opportunities, and development projects.<br />
<br />
The city of Boulder hosts thriving tech industries, supports a renowned entrepreneurial community, has some of the region's best restaurants, and is home to many federal research labs. There are endless ways to enjoy Boulder's 300-plus days of sunshine a year — from the hundreds of miles of hiking and biking trails to some of the country's finest microbrews. It's also quick and easy to get around by bus or bike and a quick 25 mile ride to nearby Denver.<br />
<br />
'''Special Instructions to Applicants''' <br/><br />
The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
== Two Postdoctoral Positions on Interpretable Vector Space Models ==<br />
*Employer: Cardiff University<br />
*Title: Postdoctoral research associate<br />
*Speciality: Neural networks, statistical relational learning, natural language processing<br />
*Location: Cardiff, UK<br />
*Deadline: November 2 2017<br />
*Date posted: October 6, 2017<br />
*Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two postdoctoral research posts at Cardiff University’s School of Computer Science & Informatics in the context of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC). The overall aims of this project are (i) to learn interpretable vector space representations of entities and their relationships, and (ii) to exploit these vector space representations for various forms of flexible reasoning with, and learning from structured data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/<br />
<br />
The aim of these positions will be to contribute to one or more of the following topics.<br />
<br />
1) Learning structured event embeddings. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with cognitively inspired representations (e.g. based on the theory of conceptual spaces). Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. <br />
<br />
2) Combining statistical relational learning with vector space models of commonsense reasoning. Low-dimensional vector space representations can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning (SRL) can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths, enabling interpretable and robust plausible reasoning from sparse relational data.<br />
<br />
3) Geometric representations of logical theories. Most vector space models for knowledge base completion simply represent entities, attributes and relations as vectors. In many domains, however, plausible inferences rely on complex dependencies that cannot be captured by such representations. As an alternative, we will develop methods in which predicates are represented as regions, and logical formulas correspond to qualitative constraints on the spatial configurations of these regions. This model will support more complex inferences than existing approaches, will allow us to exploit existing domain knowledge when learning vector space representations, and will conversely allow us derive approximate logical theories from a learned embedding.<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Salaried 4-year PhD Position in Computational Linguistics/NLP at Stockholm University ==<br />
*Employer: Stockholm University, Sweden<br />
*Title: PhD candidate<br />
*Speciality: Computational Linguistics/Natural Language Processing<br />
*Location: Stockholm, Sweden<br />
*Deadline: October 16, 2017<br />
*Date posted: September 20, 2017<br />
*Contact: [mailto:robert@ling.su.se Robert Östling]<br />
<br />
More information and application form: http://www.su.se/english/about/working-at-su/jobs?rmlang=UK&rmpage=job&rmjob=3869<br />
<br />
The Department of Linguistics at Stockholm University is looking for a new PhD candidate in the area of computational linguistics/natural language processing. PhD candidates are regular employees of Stockholm University, with a starting salary of 25,300 SEK (2,650 EUR; 3,200 USD) per month and the same benefits and social security as other University employees. The position is fully funded for 4 years. Extension up to one year is possible if the candidate performs teaching or other duties at the department, and further extension is granted in case of parental or sick leave.<br />
<br />
The choice of thesis topic is not restricted to a particular project, but should be aligned with the research profile of the department. Possible topics include multilingual NLP methods, machine translation, or computational methods for other areas of research at the department (language acquisition, linguistic typology, phonetics, sign language).<br />
<br />
Potential applicants are encouraged to contact [mailto:robert@ling.su.se Robert Östling] to discuss possible thesis projects, or other issues related to the position.<br />
<br />
== Tenure Line Assistant Professor Position in Linguistics at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Tenure Line Assistant Professor Position in Linguistics at Northwestern University<br />
*Speciality: Meaning<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2017<br />
*Date posted: September 18, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
http://www.linguistics.northwestern.edu/about/news/faculty-search.html<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line assistant professor position with a start date of September 1, 2018. We are looking for candidates with research and teaching interests in meaning, broadly construed. We are particularly interested in candidates whose research program includes cognitive, computational, and/or social approaches. The successful candidate will join a vibrant interdisciplinary community of researchers in the science of language, including computer science, philosophy, psychology, cognitive neuroscience, and speech science.<br />
<br />
To receive fullest consideration, applications should be uploaded by December 1, 2017. Candidates must hold a Ph.D. in Linguistics, Cognitive Science, Computer Science, Psychology, or a related field by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work, teaching evaluations (if available), and the names of three references (with their contact information). References will separately receive upload instructions after you have submitted your application (letters of reference should arrive as close as December 1st as possible).<br />
<br />
The Department is strongly committed to enhancing diversity, equity and inclusion in all aspects – including, but not limited to, race/ethnicity, and gender, as well as disability, sexual orientation, and gender expression and identity. We encourage applications from candidates that share this vision.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair.<br />
<br />
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11998Employment opportunities, postdoctoral positions, summer jobs2017-09-18T15:29:12Z<p>Tristan Miller: PhD-level Researchers, AIPHES, Darmstadt/Heidelberg</p>
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<br />
== PhD-level Researchers, AIPHES, Darmstadt/Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] or [http://www.cl.uni-heidelberg.de/ Ruprecht Karls University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Speciality: Natural Language Processing, Computational Linguistics, Machine Learning, or related areas<br />
* Location: Darmstadt<br />
* Deadline: October 6, 2017<br />
* Date posted: September 18, 2017<br />
* Contact: [https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/ AIPHES recruitment form]<br />
<br />
The Research Training Group [http://www.aiphes.tu-darmstadt.de/ "Adaptive Information Preparation from Heterogeneous Sources" (AIPHES)], which has been established in <br />
2015 at the Technische Universität Darmstadt and at the <br />
Ruprecht‑Karls‑University Heidelberg is filling several positions for <br />
three years, starting on April 1st, 2018. Positions remain open until <br />
filled.<br />
<br />
PhD-level Researchers in Natural Language Processing, Computational <br />
Linguistics, Machine Learning, or related areas<br />
<br />
The positions provide the opportunity to obtain a doctoral degree in <br />
the research area of the training group with an emphasis, e.g., in <br />
graph-based discourse processing, in natural language processing tasks <br />
such as automated summarization, in representation and analysis of <br />
text-induced structures, in jointly analyzing text and images, or in a <br />
related area. The group will be located in Darmstadt and Heidelberg. <br />
The funding follows the guidelines of the DFG, and the positions are <br />
paid according to the E13 public service pay scale.<br />
<br />
The goal of AIPHES is to conduct innovative research in knowledge <br />
acquisition on the Web in a cross-disciplinary context. To that end, <br />
methods in computational linguistics, natural language processing, <br />
machine learning, network analysis, computer vision, and automated <br />
quality assessment will be developed. AIPHES will investigate a novel, <br />
complex scenario for information preparation from heterogeneous <br />
sources. It interacts closely with end users who prepare textual <br />
documents in an online editorial office, and who should therefore <br />
profit from the results of AIPHES. In-depth knowledge in one of the <br />
above areas is desirable but not a prerequisite.<br />
<br />
Participating research groups at the Technische Universität Darmstadt <br />
are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge <br />
Processing (Prof. Gurevych), Machine Learning (Prof. Kersting), Visual <br />
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at <br />
Ruprecht Karls University Heidelberg are the Institute for <br />
Computational Linguistics (Prof. Frank) and the Natural Language <br />
Processing Group (Prof. Strube) of the Heidelberg Institute for <br />
Theoretical Studies (HITS). <br />
<br />
AIPHES emphasizes close contact between the students and their <br />
advisors, have regular joint meetings, a co-supervision by professors <br />
and younger scientists in the research groups, and an intensive <br />
exchange as part of the research and qualification program. The <br />
training group has the goal of publishing its results at leading <br />
scientific conferences and will actively support its doctoral <br />
researchers in this endeavor. The software that will be developed in <br />
the course of AIPHES should be put under the open source Apache <br />
Software License 2.0 if possible. Moreover, the research papers and <br />
datasets should be published with open access models.<br />
<br />
Prerequisites<br />
<br />
We are looking for exceptionally qualified candidates with a degree in <br />
Computer Science, Computational Linguistics, or a related study <br />
program. We expect ability to work independently, personal commitment, <br />
team and communication abilities, as well as the willingness to <br />
cooperate in a multi-disciplinary team. Desirable is experience in <br />
scientific work. Applicants should be willing to work with <br />
German-language texts, and, if necessary, to acquire German language <br />
skills during the training program. We specifically invite applications <br />
of women. Among those equally qualified, handicapped applicants will <br />
receive preferential consideration. International applications are <br />
particularly encouraged.<br />
<br />
The Department of Computer Science of [https://www.informatik.tu-darmstadt.de/ TU Darmstadt] is regularly <br />
ranked among the top ones in respective rankings of German <br />
universities. The [http://www.cl.uni-heidelberg.de/ Institute for Computational Linguistics (ICL) of the <br />
Ruprecht Karls University Heidelberg] is one of the largest centers <br />
for computational linguistics both in Germany and internationally. The <br />
ICL and the NLP department of the HITS jointly run the graduate <br />
program [http://semproc.cl.uni-heidelberg.de/ “Semantic Processing”] with an integrated research training <br />
group “Coherence in language processing: Semantics beyond the <br />
sentence”, which has a close connection to the topics in computational <br />
linguistics of AIPHES.<br />
<br />
Applications should include a motivational letter that refers to one <br />
or two of the planned research areas of [http://www.aiphes.tu-darmstadt.de/ AIPHES], a CV with <br />
information about the applicant’s scientific work, certifications of <br />
study and work experience, as well as a thesis or other publications in <br />
electronic form. Application materials should be submitted via the <br />
following form by October 6th, 2017: <br />
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/. In <br />
addition, applicants should be prepared to solve a programming and a <br />
reviewing task in the first two weeks after their application.<br />
<br />
<br />
==Postdoc Position on Sentence Understanding and Generation at NYU==<br />
<br />
* Employer: New York University, Machine Learning for Language Group (Sam Bowman and Kyunghyun Cho)<br />
* Title: Postdoc <br />
* Specialty: Sentence understanding and generation using deep neural networks with latent tree structures or other latent variables<br />
* Location: New York, NY, USA<br />
* Deadline: Rolling<br />
* Date posted: September 15, 2017<br />
* Contact: [mailto:bowman@nyu.edu Sam Bowman]<br />
<br />
The Machine Learning for Language Group at NYU expects to hire at least one postdoc to start some time in 2018, working with one or both of PIs Kyunghyun Cho and Sam Bowman.<br />
<br />
We expect the researcher to use their time here to develop an independent research program which involves work on neural network models for natural language understanding or generation at the sentence level and to also participate in work on models which use latent tree structures or other continuous or discrete latent variables. The position will be funded through a sponsored research agreement on this topic, and while the researcher may be asked to contribute some effort to the completion of the sponsored research, this shouldn’t be a burden: It will only involve the development, evaluation and publication of novel modeling methods on public datasets.<br />
<br />
For more details, see the full ad here:<br />
<br />
https://wp.nyu.edu/ml2/postdoc-opening/<br />
<br />
==PhD Position on Adaptive Text Generation in a Serious Game, The Netherlands==<br />
<br />
* Employer: University of Twente<br />
* Title: PhD position <br />
* Specialty: Natural Language Generation<br />
* Location: Enschede, The Netherlands<br />
* Deadline: 28 August, 2017<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:m.theune@utwente.nl Mariët Theune]<br />
<br />
The research group Human Media Interaction of the University of Twente is looking for a PhD candidate to work on adaptive text generation. The PhD research aims at generating natural language texts in Dutch, for use in a training game for Dutch firefighters. The texts will be adaptive in the sense that they will be tailored to the player’s individual needs and competences. The type of narrative game that will be developed in our project (in collaboration with a serious game company) offers multiple opportunities for such tailoring of textual game content. Specifically, the goal is to work on the generation of in-game texts based on current real-world data, the generation of non-player character dialogue and the generation of post-game narrative feedback on player performance. Since the generated texts will be in Dutch, the PhD candidate is expected to have a good command of the Dutch language.<br />
<br />
The position is full-time for four years. Starting date is as soon as possible. Find more details about the position, including how to apply, by clicking on the link below:<br />
<br />
https://www.utwente.nl/en/organization/careers/vacancies/!/vacature/1155511<br />
<br />
==Permanent Position for Postdocs in Machine Learning & NLP, Paris, France==<br />
<br />
* Employer: SPARTED<br />
* Title: Project Researcher <br />
* Specialty: NLP, Machine Learning, Deep Learning, Information Extraction<br />
* Location: Paris (16), France<br />
* Deadline: Until candidate is found<br />
* Date posted: August 4, 2017<br />
* Contact: [mailto:camille@sparted.com]; phone [+33] (06)52148693<br />
* Website: http://www.sparted.com<br />
<br />
SPARTED is an innovative and disruptive French EdTech startup that is changing the way people learn by turning employees into daily learners. We offer companies and organizations a SaaS micro-learning mobile platform that allows them to create online gamified content and deliver it independently in a white label app.<br />
SPARTED is initiated an ambitious project and is hiring a Postdoc researcher to pilot it. Find more details about the position by clicking on the link below:<br />
<br />
http://files.sparted.com/all/Job%20description/AI%20FICHE%20DE%20POSTE.pdf<br />
<br />
== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==<br />
<br />
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain <br />
* Title: PhD Scholarship<br />
* Specialty: Text Mining, Information Extraction, Music Information Retrieval<br />
* Location: Barcelona, Spain<br />
* Deadline: Until candidate is found<br />
* Date posted: June 10, 2017<br />
* Contact: [mailto:horacio.saggion@upf.edu]<br />
<br />
<br />
PhD position on data-driven methodologies for music knowledge extraction<br />
In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.<br />
<br />
Supervisors of the position: Xavier Serra and Horacio Saggion<br />
Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)<br />
<br />
The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.<br />
<br />
The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .<br />
<br />
<br />
== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11858Employment opportunities, postdoctoral positions, summer jobs2017-05-03T12:41:01Z<p>Tristan Miller: Scientific System Developer, UKP Lab, TU Darmstadt</p>
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== Scientific System Developer, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Scientific System Developer<br />
* Specialty: Argument Mining, Machine Learning, Big Data Analysis<br />
* Location: Darmstadt<br />
* Deadline: May 31, 2017<br />
* Date posted: May 3, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a<br />
<br />
'''Scientific System Developer'''<br><br />
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''<br />
<br />
to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners. <br />
<br />
We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297<br />
We look forward to receiving your application!<br />
<br />
<br />
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==<br />
<br />
* Employer: Cardiff University<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI<br />
* Location: Cardiff, UK<br />
* Deadline: May 20, 2017<br />
* Date posted: April 20, 2017<br />
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]<br />
<br />
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:<br />
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.<br />
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval. <br />
<br />
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. <br />
<br />
<br />
'''More information'''<br />
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
<br />
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==<br />
<br />
* Employer: University of Colorado Boulder<br />
* Title: Postdoctoral Research Associate<br />
* Specialty: Advanced Machine Learning<br />
* Location: Boulder, Colorado, United States<br />
* Deadline: Ongoing, desired start Summer/Fall 2017<br />
* Date posted: March 31, 2017<br />
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/><br />
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)<br />
<br />
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.<br />
<br />
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.<br />
<br />
'''Required'''<br />
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)<br />
* Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)<br />
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record<br />
<br />
'''Desired'''<br />
* Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)<br />
* Experience mentoring graduate and undergraduate students<br />
<br />
'''Job Details'''<br />
* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.<br />
* Start date is negotiable, but anticipated for Summer/Fall 2017.<br />
* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.<br />
<br />
'''How to apply''' <br/><br />
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.<br />
<br />
Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.<br />
<br />
The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].<br />
<br />
'''Questions''' <br/><br />
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]<br />
<br />
<br />
== Researcher in Machine Learning and NLP, DFKI, Germany ==<br />
<br />
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany<br />
* Title: Researcher<br />
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation<br />
* Location: Saarbruecken<br />
* Deadline: March 31, 2017<br />
* Date posted: March 13, 2017<br />
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]<br />
<br />
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.<br />
<br />
'''Key research responsibilities''' include:<br />
* machine and deep learning for natural language processing/machine translation<br />
* software development and integration<br />
* publication in top-tier conferences and journals<br />
<br />
'''General responsibilities''' include:<br />
* engagement with industry partners and contract research <br />
* identification of funding opportunities and engagement in proposal writing<br />
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations<br />
* administrative work associated with programmes of research<br />
<br />
'''Requirements:'''<br />
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar<br />
* Strong background and track record in machine learning, neural nets and deep learning<br />
* Strong background and track record in NLP and MT - Excellent programming skills<br />
* Excellent problem solving skills, independent and creative thinking<br />
* Excellent team working and communication skills<br />
* Excellent command of written and oral English<br />
* Command of German and other languages not a requirement but helpful<br />
<br />
The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).<br />
<br />
'''Working environment:'''<br />
DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.<br />
<br />
The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project [http://www.qt21.eu/ QT21] on MT, the EU CEF funded [http://lr-coordination.eu/ ELRC] project and the EU funded [http://www.tradr-project.eu/ TRADR] project on human-robot collaboration in disaster response scenarios.<br />
<br />
The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in [http://www.mmci.uni-saarland.de/en/start Multimodal Computing and Interaction] and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.<br />
<br />
'''Geographical environment:'''<br />
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.<br />
<br />
'''Starting date, duration, salary:'''<br />
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.<br />
<br />
'''Application:'''<br />
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11785Employment opportunities, postdoctoral positions, summer jobs2017-02-21T11:28:07Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
<hr />
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== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning<br />
* Location: Darmstadt<br />
* Deadline: March 8, 2017<br />
* Date posted: February 21, 2017<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine <br />
Learning (IML) or Natural Language Processing for Language Learning. <br />
The UKP Lab is a research group comprising over 30 team members who <br />
work on various aspects of Natural Language Processing (NLP), of <br />
which Interactive Machine Learning and Natural Language Processing <br />
for Language Learning are the focus areas researched in collaboration <br />
with partners in research and industry.<br />
<br />
We ask for applications from candidates in Computer Science with a <br />
specialization in Machine Learning or Natural Language Processing, <br />
preferably with expertise in research and development projects, and <br />
strong communication skills in English and German.<br />
<br />
* The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes. <br />
* The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems. <br />
<br />
Prior work in the above areas is a definite advantage. Ideally, the <br />
candidates should have demonstrable experience in designing and <br />
implementing complex (NLP and/or ML) systems, experience in <br />
large-scale data analysis, large-scale knowledge bases, and strong <br />
programming skills incl. Java. Experience with neural network <br />
architectures and a sense for user experience design are a strong <br />
plus. Combining fundamental NLP research on Interactive Machine <br />
Learning or Natural Language Processing with practical applications <br />
in different domains including education will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community <br />
and with partners from research and industry provides an excellent <br />
environment for the position to be filled. The Department of Computer <br />
Science of TU Darmstadt is regularly ranked among the top ones in <br />
respective rankings of German universities. Its unique research <br />
initiative "Knowledge Discovery in the Web" and the Research Training <br />
Group [https://www.aiphes.tu-darmstadt.de/ "Adaptive Information Processing of Heterogeneous Content" (AIPHES)] funded by the DFG emphasize NLP, machine learning, text <br />
mining, as well as scalable infrastructures for the assessment and <br />
aggregation of knowledge. UKP Lab is a highly dynamic research group <br />
committed to high-quality research results, technologies of the <br />
highest industrial standards, cooperative work style and close <br />
interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an <br />
outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things <br />
being equal, candidates with disabilities will be given preference. <br />
Please send the applications to: <br />
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions <br />
are open until filled. Later applications may be considered if the <br />
position is still open.<br />
<br />
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==<br />
*Employer: Northwestern University, USA<br />
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: April 1, 2017<br />
*Date posted: February 17, 2017<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).<br />
<br />
The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.<br />
<br />
To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==<br />
*Employer: Cardiff University, UK<br />
*Title: Research Associate in Artificial Intelligence / Machine Learning<br />
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models<br />
*Location: Cardiff, UK<br />
*Deadline: March 2, 2017<br />
*Date posted: February 13, 2017<br />
*Contact: schockaerts1@cardiff.ac.uk<br />
<br />
Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience. <br />
<br />
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)<br />
<br />
'''Essential criteria'''<br />
<br />
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience<br />
* An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.<br />
* A strong background in statistics and linear algebra.<br />
* Excellent programming skills.<br />
* Knowledge of current status of research in specialist field.<br />
* Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP). <br />
* Ability to understand and apply for competitive research funding.<br />
* Proven ability in effective and persuasive communication.<br />
* Ability to supervise the work of others to focus team efforts and motivate individuals.<br />
* Proven ability to demonstrate creativity, innovation and team-working within work.<br />
<br />
'''Background about the university'''<br />
<br />
Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework. <br />
<br />
'''Background about the project'''<br />
<br />
Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications. <br />
<br />
The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.<br />
<br />
'''More information'''<br />
<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.<br />
<br />
== Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associates in Natural Language Processing / Text Mining<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: March 13, 2017<br />
*Date posted: February 10, 2017<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.<br />
<br />
They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning. <br />
<br />
'''Skills'''<br />
<br />
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java. <br />
<br />
* Duration of post: Immediately until 31st October 2018<br />
* Salary: £31,076-£38,183 per annum<br />
<br />
'''Research Team'''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk). <br />
<br />
Deadline of applications: 13/03/2017<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975 <br />
<br />
<br />
== Research Scientist Intern at Adobe Research, San Jose, California ==<br />
*Employer: Adobe Systems Incorporated<br />
*Title: Research Scientist Intern <br />
*Speciality: NLP, machine learning and dialog.<br />
*Location: San Jose, CA, USA<br />
*Deadline: March 1, 2017<br />
*Date posted: January 23, 2017<br />
*Contact: bui@adobe.com<br />
<br />
We are looking for PhD students with background in NLP, machine learning, dialog to work on 2 following projects:<br />
1) Deep reinforcement learning for creative assistant<br />
2) Reading order text extraction for PDF documents<br />
<br />
== Assistant/Associate Professor Position in NLP/IR/Text/ML at University of California - Davis ==<br />
*Employer: University of California - Davis<br />
*Title: Assistant/Associate Professor <br />
*Speciality: All areas of NLP/Text/IR/ML etc including those involved in multi-media analysis.<br />
*Location: Davis, CA, USA<br />
*Deadline: January 2, 2017<br />
*Date posted: December 27, 2016<br />
*Contact: davidson@cs.ucdavis.edu<br />
<br />
The Department of Computer Science at the University of California at Davis invites applications for a faculty position at the rank of Assistant or Associate Professor in Computer Science, for appointments with a start date in Spring 2017, or later. We are targeting excellent candidates in all areas of machine learning and computational linguistics, with a special emphasis on all aspects of natural language processing, information retrieval, text analytics and text mining. The campus is especially interested in candidates who can contribute to the diversity and excellence of the academic community through their research, teaching, and service.<br />
<br />
Applications received by 2nd January 2017 will receive full consideration. For further information see http://www.cs.ucdavis.edu/blog/faculty-employment-positions-2/<br />
<br />
<br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / Machine Learning at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Machine Learning, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: December 23, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians led by Dr. Leonid Perlovsky (http://www.leonid-perlovsky.com/) and Dr. Alexander Turchin (https://connects.catalyst.harvard.edu/Profiles/display/Person/14588) on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI; Leonid Perlovsky, PhD<br />
<br />
'''Required skills''': strong mathematical background in statistics and machine learning; experience working with large datasets; experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with predictive modeling, medical terminologies / ontologies, python, MATLAB and Apache Spark is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, or related discipline or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels (https://grants.nih.gov/grants/guide/notice-files/NOT-OD-16-131.html).<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.<br />
<br />
<br />
== PhD Scholarship / Enhancing Scientific Text Summarization / Barcelona ==<br />
*Title: PhD Scholarship / Enhancing Scientific Text Summarization with Academic Social Networks<br />
*Location: Barcelona, Spain<br />
*Deadline: February 2nd, 2017<br />
*Date posted: December 12, 2016<br />
*Contact: horacio.saggion@upf.edu<br />
<br />
In the context of the Marie-Curie PhD InPhiNIT La Caixa program associated to the Maria de Maeztu Strategic Research Program, we are looking for a highly motivated PhD candidate in the area of Natural Language Processing to work in a project dealing with Scientific Text Summarization and Academic Social Networks. <br />
<br />
The PhD will be carried out at the TALN research group of the Department of Information and Communication Technologies (DTIC), Universitat Pompeu Fabra (UPF) in Barcelona.<br />
<br />
The PhD student should have background in Natural Language Processing with a solid knowledge of statistics, mathematics, computer programming and machine learning. Experience in Information Extraction, Text Summarization, or related areas would be appreciated.<br />
<br />
Brief description of the project:<br />
<br />
http://www.dtic.upf.edu/~hsaggion/scientific_summarization_social.html<br />
<br />
How and where to apply (InPhiNIT program):<br />
<br />
https://obrasociallacaixa.org/en/educacion-becas/becas-de-posgrado/inphinit/programme-description<br />
<br />
<br />
<br />
The TALN research group:<br />
<br />
http://taln.upf.edu/<br />
<br />
Maria de Maeztu Strategic Research at DTIC:<br />
<br />
https://www.upf.edu/web/mdm-dtic/description<br />
<br />
http://ec.europa.eu/research/mariecurieactions/<br />
<br />
Other:<br />
<br />
You can contact Prof. Horacio Saggion for more information about the project.<br />
<br />
Related information:<br />
<br />
https://www.upf.edu/web/mdm-dtic/projects/-/asset_publisher/Ef1was9TxNY4/content/id/4113025#.WE6ZIH23nm4<br />
<br />
http://taln.upf.edu/pages/coling2016tutorial/<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
== Lecturer/Senior Lecturer openings in Artificial Intelligence and Machine Learning at Imperial College London, UK ==<br />
*Employer: Department of Computing, Imperial College London<br />
*Title: Lecturer/Senior Lecturer openings in Artificial Intelligence and Machine Learning<br />
*Speciality: Artificial Intelligence and Machine Learning, including (but is not limited to): machine learning for text and speech.<br />
*Location: London, UK<br />
*Deadline: January 16, 2017<br />
*Date posted: December 8, 2016<br />
*Contact: margaret.hall@imperial.ac.uk<br />
<br />
The Department of Computing at Imperial College London invites applications for full-time faculty members at the Lecturer/Senior Lecturer level (comparable to American tenure-track Assistant Professorships) who can contribute to research and teaching, in particular in the area of Artificial Intelligence and Machine Learning. This includes (but is not limited to): autonomous systems; knowledge representation and reasoning; planning; machine learning for speech, audio and text; optimization and data mining.<br />
<br />
Notwithstanding the above focus, exceptional candidates from any area of Computer Science are also encouraged to apply.<br />
<br />
The deadline for applications is 16th January 2017. For further information see http://www.imperial.ac.uk/computing/job-vacancies/<br />
<br />
<br />
== Research Fellow in Biomedical Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Fellow<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: December 18, 2016<br />
*Date posted: November 28, 2016<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a postdoctoral research fellow in Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester. The position is for 2 years.<br />
<br />
The objective of this BBSRC funded post is to conduct research into extracting complex information (entities and events) from the scientific literature to support metabolic model development.<br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in biomedical text mining (event extraction); excellent knowledge in developing and adapting algorithms for text mining systems; strong publication record; excellent programming skills.<br />
<br />
* Duration of post: 1st January 2017 to 31st December 2018<br />
* Salary: £39,324 to £48,327 per annum<br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems.<br />
NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
<br />
The project will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics.<br />
More information about the project: http://www.nactem.ac.uk/empathy/<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).<br />
<br />
Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12531<br />
<br />
<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: December 12, 2016<br />
* Date posted: November 23, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine Learning (IML) or Computational Argumentation (CA). The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Interactive Machine Learning and Computational Argumentation are the rapidly developing focus areas in collaboration with partners in research and industry. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German. <br />
- The successful applicant in the area of interactive machine learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create the corresponding product prototypes. <br />
- The successful applicant in the area of Computational Argumentation will work on research activities in analyzing the discourse of future professionals while reasoning to automatically access their argumentation quality given small amounts of training data, and development activities for the research prototype. <br />
Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems, experience in information retrieval, large-scale data processing and large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures is a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Computational Argumentation with practical applications in different domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” and the Research Training Group [https://www.aiphes.tu-darmstadt.de “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 15.12.2016. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== One Teaching Track and One Tenure Track position open at the Language Technologies Institute at Carnegie Mellon University (Pittsburgh, PA USA) ==<br />
Employer: Language Technologies Institute, School of Computer Science, Carnegie Mellon University<br />
<br />
Title: Assistant Teaching Professor and Assistant Professor<br />
<br />
Specialty: Natural Language Processing, Computational Linguistics, Machine Learning and Statistical Methods for NLP, Social Media Analysis<br />
* Deadline: January 3, 2017<br />
* Date posted: 10th November 2016<br />
* Contact: [mailto:cprose@cs.cmu.edu Dr. Carolyn P.Rose]<br />
<br />
The Language Technologies Institute (LTI) in the School of Computer Science (SCS) at Carnegie Mellon University invites applications for teaching-track and tenure-track positions, beginning Fall 2017. LTI is an academic department dedicated to the study of human language and information technologies, with approximately thirty faculty members. LTI is one of seven departments within SCS, which has over 200 tenure-track, research, and teaching faculty with expertise spanning traditional computer science, human computer interaction, language technologies, machine learning, computational biology, software engineering, and robotics. SCS offers a highly collaborative and uniquely interdisciplinary environment that promotes innovation and entrepreneurship in both teaching and research. <br />
<br />
<br />
The teaching track is a career-oriented, renewable appointment with an initial appointment of three years. Initial teaching-track appointments are typically at the rank of Assistant Teaching Professor, with the possibility of promotion to the ranks of Associate Teaching Professor and Teaching Professor. These ranks are not tenured, but they do provide substantial opportunities for professional growth and long-term contributions to Language Technologies education at Carnegie Mellon University. Teaching track faculty contribute to the design of new curricula and the adoption of new teaching methods.<br />
For more information about this position, see: http://lti.cs.cmu.edu/teaching-track-faculty-position<br />
<br />
<br />
We are also seeking to hire on the tenure track. Tenure track appointments are typically at the rank of Assistant Professor, with the possibility of promotion to the ranks of Associate Professor and Professor. Tenure-track applicants must have strong interests and accomplishments in both research and teaching. For more information about this position, see: http://lti.cs.cmu.edu/tenure-track-faculty-position<br />
<br />
== One Post-doctoral position in Statistical Machine Translation in CUNY (at Manhattan, NYC) ==<br />
<br />
Employer: Department of Computer Science at Hunter College, University of New York<br />
Title: post-doctoral position<br />
Specialty: Machine Translation <br />
Location: Manhattan, NYC, NY<br />
* Deadline: Open until filled <br />
* Date posted: 6th November 2016<br />
* Contact: [mailto:Jia.Xu@hunter.cuny.edu Dr. Jia Xu]<br />
<br />
The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for one post-doctoral position. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.<br />
<br />
Applicants should hold by the time the appointment begins a PhD (or its equivalent) in Computer Science, Computer Engineering, Statistics, Mathematics, Physics or in a related discipline. We are seeking for applicants committed to either (1) extending their current research program in statistical Natural Language Processing or (2) employing their analytical and engineering skills and join in our current research program. Therefore, this position can be also seen as an opportunity to fast-forward develop statistical NLP skills and conduct cutting-edge research in this field.<br />
<br />
The position is for 1 year with the possibility of extending it up to 3 years. The starting date is flexible.<br />
<br />
The Hunter College at the City University of New York may ask the post-doctor to take up a very moderate teaching load (can be waived based on research promise). The salary commensurate with qualifications and research potential and starts from $50K/year.<br />
<br />
Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for collaboration. Hunter college is surrounded by top research labs (e.g. Google Research, Microsoft Research, Facebook, IBM Research), and many other university departments (e.g. Princeton, Columbia, NYU).<br />
<br />
Applications should include a recent CV and optionally a research statement and 2 representative publications. Applications should be sent to Dr. Jia Xu by email to: jia.xu@hunter.cuny.edu including in the Subject title the keyword: “Application”.<br />
<br />
All applicants will be notified upon receipt of the application by email.<br />
<br />
This position will be advertised at http://jiaxu.org until is filled.<br />
<br />
Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.<br />
<br />
<br />
<br />
== Three fully funded PhD Positions in Statistical Natural Language Processing in CUNY (at Manhattan, NYC) ==<br />
<br />
Employer: Department of Computer Science at Hunter College, University of New York<br />
Title: fully-funded PhD position<br />
Specialty: NLP<br />
* Location: Manhattan, NYC, NY<br />
* Deadline: Open until filled <br />
* Date posted: 6th November 2016<br />
* Contact: [mailto:Jia.Xu@hunter.cuny.edu Dr. Jia Xu]<br />
<br />
<br />
The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for fully-funded PhD student positions starting in 2017. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.<br />
<br />
Applicants should hold by the time that begin their PhD studies a BSc, BEng (or its equivalent) in Computer Science, Linguistics, Computer Engineering, Statistics, Mathematics, Physics or related disciplines. We are seeking for very motivated students with enthusiasm and dedication in conducting cutting-edge research in statistical methods over massive amounts of data. Natural Language Processing is the prototypical domain where Machine Learning and Big Data are required to come together.<br />
<br />
The typical duration of the PhD program is from 3 to 4 years. <br />
<br />
The Hunter College at the City University of New York asks that the PhD candidate should take up two teaching assistantships per year. The admitted student will be offered to have the tuition fees covered and also stipend sufficient to cover the living cost.<br />
<br />
Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for internships and collaboration. Hunter college is surrounded by top research labs, such as Google Research, Microsoft Research, Facebook, and IBM Research.<br />
<br />
Application material: CV and optionally a statement of purpose letter, GRE, and TOELF/IELTS results. Applications should be sent to Dr. Jia Xu by email to: Jia.Xu@hunter.cuny.edu including in the Subject title the keyword: “PhD".<br />
<br />
All applicants will be notified upon receipt of the application by email.<br />
<br />
This position will be advertised at http://jiaxu.org until the position is filled.<br />
<br />
Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.<br />
<br />
<br />
<br />
== Funded PhD Position in Natural Language Processing in Barcelona ==<br />
<br />
* Employer: Department of Information and Communication Technologies at Universitat Pompeu Fabra<br />
* Title: PhD studentship position<br />
* Specialty: NLP<br />
* Location: Barcelona, Spain<br />
* Deadline: August 8th, 2016 (or until filled) <br />
* Date posted: 29th July 2016<br />
* Contact: [mailto:horacio.saggion@upf.edu Prof. Horacio Saggion]<br />
<br />
<br />
The Department of Information and Communication Technologies at Universitat Pompeu Fabra in Barcelona, Spain, invites applications for a PhD studentship position that is associated with the María de Maeztu Units of Excellence Research Program of the Spanish Government (http://www.upf.edu/mdm-dtic), and involves joint work of the research labs of profs. Horacio Saggion and Ricardo Baeza-Yates. This position will be funded under the FPI call to be launched by the Spanish Ministry of Economy and Competitiveness.<br />
<br />
Project Description<br />
<br />
In the context of our Maria de Maeztu (MdM) project "Mining the Knowledge of Scientific Publications" ( see http://www.upf.edu/mdm-dtic) the PhD student will carry out a research project on the more focused area of automatic research paper assessment which concerns a number of interesting research questions including but not limited to: <br />
<br />
* automatic research paper evaluation<br />
* automatic research paper/author impact prediction<br />
* automatic novelty evaluation<br />
<br />
The PhD will benefit from the resources developed during MdM project: availability of large scale open scientific repositories, natural language processing technology adapted to scientific text processing, document retrieval technology, etc. as well as the expertise of the MdM team members.<br />
<br />
Applicants<br />
<br />
Candidates should hold a M.Sc. in Computer Science or related field with a solid background in Natural Language Processing and be proficient in spoken and written English. Experience with recent advances in Machine Learning and Information Retrieval would be highly valuable. Knowledge of statistical analysis is highly desirable.<br />
<br />
More information<br />
<br />
For informal inquiries, prospective candidates may contact professor Horacio Saggion at horacio DOT saggion AT upf DOT edu <br />
<br />
For more information please check the official announcement at <br />
<br />
https://portal.upf.edu/web/etic/automatic-research-assessment?p_p_id=56_INSTANCE_MaAxd6TFfhia&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&p_p_col_id=column-1&p_p_col_count=1<br />
<br />
== Research Fellow in Biomedical Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Fellow<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: August 13, 2016<br />
*Date posted: July 18, 2016<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a postdoctoral research fellow in Biomedical Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester.<br />
<br />
The objective of this BBSRC funded post in collaboration with Unilever is to conduct research into extracting complex information from the scientific literature to support metabolic pathway curation using text mining methods. <br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, etc., and in high quality journals; excellent programming skills; proven ability to develop independently research proposals. <br />
<br />
* Duration of post: until 31st March 2018 with possibility of extension<br />
* Salary: £38,896 to £47,801 per annum<br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems.<br />
NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
<br />
The project will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics.<br />
More information about the project: http://www.nactem.ac.uk/empathy/<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).<br />
<br />
Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=11856<br />
<br />
== Computational Linguist-Morphology ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist-Morphology<br />
* Specialty: Application of Finite State Transducers (FST) to language processing technologies, development of FST networks for languages, integration of morphological analyzers.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist-Morphology provides unique expertise with the application of FST to language processing technologies, to include the development of FST networks for languages, the integration of morphological analyzers in multilingual databases/search engines and the development of APIs for managing FST I/O in a multilingual environment.<br />
<br />
''Qualifications''<br />
<br />
*A master's degree in computer science and/or linguistics, or in a related field; eight (8) years related experience in FST technologies for language applications may be substituted for a master's degree.<br />
<br />
*Within the last ten (10) years, shall have a minimum of seven (7) years experience programming language networks in one or more FST applications such as XSFT, Stuttgart Finite State Transducer Toolkit, OpenFST, FOMA, or other product with equivalent functional capabilities.<br />
<br />
*Shall have a minimum of five (5) years experience coding with two (2) or more of the following: C, C++, or Java. Shall also have a minimum of five (5) years experience with Perl and/or Python scripting languages.<br />
<br />
*Within the last ten (10) years, shall have a minimum of five (5) years experience with linguistics and language structure, language processing technologies, and/or with applying morphologies to multilingual databases/search engines.<br />
<br />
*Shall have a minimum of five (5) years experience with two (2) or more foreign languages. Shall have demonstrated experience with international encodings, to include converting and handling multilingual encoding, such as UTF-8.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist-Morphology".<br />
<br />
== Computational Linguist ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist<br />
* Specialty: Integration of NLP Modules, Experimentation with User Interfaces for Analytic Support, Web Services for Querying Extracted Results.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist provides unique expertise with the application of computer science to language processing technologies, to include experimentation with, and integration of, unique NLP modules, experimentation with user interfaces for analytic support, web development, and development of web services for querying extracted results. <br />
<br />
''Qualifications''<br />
<br />
*MA in computer science and/or linguistics, or in a related field (8 years related experience may be substituted for a Master's Degree). <br />
<br />
*Within the last 10 years shall have a minimum of 7 years experience each programming: C, C++, or Java.<br />
<br />
*Within the last 5 years, shall have a minimum of 3 years programming with two or more scripting languages (e.g. Perl, Python).<br />
<br />
*Within the last 10 years, shall have a minimum of 5 years experience with linguistics and language structure, language processing technologies, and/or with applying ontologies to NLP applications. <br />
<br />
*A minimum of 5 years experience with two or more foreign languages is required. <br />
<br />
*Shall have demonstrated experience developing software in a Linux environment, with Semantic Web technologies (e.g. RDF, OWL), and with international encodings, to include converting and handling multilingual encoding, such as UTF - 8 is required.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist".<br />
<br />
== Research Associate/Fellow in Machine Learning, University of Sheffield, UK ==<br />
* Employer: [http://www.sheffield.ac.uk/ University of Sheffield], UK<br />
* Title: Research Associate/Fellow<br />
* Specialty: ML<br />
* Location: Sheffield<br />
* Deadline: July 18, 2016<br />
* Date posted: June 17, 2016<br />
* Contact: [mailto:l.specia@sheffield.ac.uk Prof. Lucia Specia]<br />
<br />
<br />
We have an opening for a 3-year position of Research Associate or Research Fellow in Machine Learning with applications to Machine Translation and Multimodal Language Processing. This position is funded by the ERC MultiMT project: Multi-modal Context Modelling for Machine Translation, led by Prof. Lucia Specia (www.dcs.shef.ac.uk/~lucia) at the University of Sheffield.<br />
<br />
This is a highly interdisciplinary project involving Natural Language Processing, Computer Vision and Machine Learning. Its goal is to devise methods and algorithms to exploit global multi-modal information for context modelling in Machine Translation. The post holder will be expected to investigate new ways to acquire multilingual multi-modal representations, and new machine learning and inference algorithms that can learn from these rich context models to generate high quality translations. In addition, if appointed as Research Fellow, the post holder will be expected to make significant contributions to multi-modal language processing in general, drawing from their experience in Computer Vision and Natural Language Processing.<br />
<br />
This is an opportunity to work in a well-connected international team with world-leading reputation in the Natural Language Processing (NLP) research group at the University of Sheffield. The NLP group is well known internationally for its research, and is one of the largest research groups in the area in Europe.<br />
<br />
This post offers excellent opportunities for publications, project visits and conference trips. Applicants should have (for Research Associate (RA) and Research Fellow (RF) posts):<br />
<br />
* PhD (or equivalent work experience) in Computer Science, Statistics, Mathematics or related areas<br />
* Significant experience and track record in Machine Learning (RA and RF)<br />
* Strong publication record commensurate with career stage (RA and RF)<br />
* Experience and strong track record in Computer Vision (desirable for RA, required for RF)<br />
* Experience and strong track record in Natural Language Processing (desirable for both RA and RF)<br />
* Strong programming experience, particularly in Python or C++. (RA and RF)<br />
<br />
This post is fixed-term with a start date from August 2016 (or soon after) and duration of ''3 years'' with possibility of extension to ''5 years''.<br />
<br />
'''Salary range''': £28,847 to £46,414 per annum.<br />
<br />
For informal inquiries contact Dr. Lucia Specia: L.Specia@sheffield.ac.uk<br />
<br />
For more information about the post and for '''applications''': http://www.shef.ac.uk/jobs, Search and apply for jobs using reference number UOS014018<br />
<br />
<br />
<br />
== Doctoral Researcher at UKP/KRITIS, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a '''Doctoral Researcher''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
'''Working environment and conditions:''' KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by '''10 July 2016'''. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11695Employment opportunities, postdoctoral positions, summer jobs2016-11-23T17:26:11Z<p>Tristan Miller: Associate Research Scientist, UKP Lab, TU Darmstadt</p>
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<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: December 12, 2016<br />
* Date posted: November 23, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an<br />
<br />
'''Associate Research Scientist'''<br /><br />
'''(PostDoc- or PhD-level; for an initial term of two years)'''<br />
<br />
to strengthen the group’s profile in the areas of Interactive Machine Learning (IML) or Computational Argumentation (CA). The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Interactive Machine Learning and Computational Argumentation are the rapidly developing focus areas in collaboration with partners in research and industry. <br />
<br />
We ask for applications from candidates in Computer Science with a specialization in Machine Learning or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German. <br />
- The successful applicant in the area of interactive machine learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create the corresponding product prototypes. <br />
- The successful applicant in the area of Computational Argumentation will work on research activities in analyzing the discourse of future professionals while reasoning to automatically access their argumentation quality given small amounts of training data, and development activities for the research prototype. <br />
Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems, experience in information retrieval, large-scale data processing and large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures is a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Computational Argumentation with practical applications in different domains will be highly encouraged.<br />
<br />
UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” and the Research Training Group [https://www.aiphes.tu-darmstadt.de “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 15.12.2016. The positions are open until filled. Later applications may be considered if the position is still open.<br />
<br />
== One Teaching Track and One Tenure Track position open at the Language Technologies Institute at Carnegie Mellon University (Pittsburgh, PA USA) ==<br />
Employer: Language Technologies Institute, School of Computer Science, Carnegie Mellon University<br />
<br />
Title: Assistant Teaching Professor and Assistant Professor<br />
<br />
Specialty: Natural Language Processing, Computational Linguistics, Machine Learning and Statistical Methods for NLP, Social Media Analysis<br />
* Deadline: January 3, 2017<br />
* Date posted: 10th November 2016<br />
* Contact: [mailto:cprose@cs.cmu.edu Dr. Carolyn P.Rose]<br />
<br />
The Language Technologies Institute (LTI) in the School of Computer Science (SCS) at Carnegie Mellon University invites applications for teaching-track and tenure-track positions, beginning Fall 2017. LTI is an academic department dedicated to the study of human language and information technologies, with approximately thirty faculty members. LTI is one of seven departments within SCS, which has over 200 tenure-track, research, and teaching faculty with expertise spanning traditional computer science, human computer interaction, language technologies, machine learning, computational biology, software engineering, and robotics. SCS offers a highly collaborative and uniquely interdisciplinary environment that promotes innovation and entrepreneurship in both teaching and research. <br />
<br />
<br />
The teaching track is a career-oriented, renewable appointment with an initial appointment of three years. Initial teaching-track appointments are typically at the rank of Assistant Teaching Professor, with the possibility of promotion to the ranks of Associate Teaching Professor and Teaching Professor. These ranks are not tenured, but they do provide substantial opportunities for professional growth and long-term contributions to Language Technologies education at Carnegie Mellon University. Teaching track faculty contribute to the design of new curricula and the adoption of new teaching methods.<br />
For more information about this position, see: http://lti.cs.cmu.edu/teaching-track-faculty-position<br />
<br />
<br />
We are also seeking to hire on the tenure track. Tenure track appointments are typically at the rank of Assistant Professor, with the possibility of promotion to the ranks of Associate Professor and Professor. Tenure-track applicants must have strong interests and accomplishments in both research and teaching. For more information about this position, see: http://lti.cs.cmu.edu/tenure-track-faculty-position<br />
<br />
== One Post-doctoral position in Statistical Machine Translation in CUNY (at Manhattan, NYC) ==<br />
<br />
Employer: Department of Computer Science at Hunter College, University of New York<br />
Title: post-doctoral position<br />
Specialty: Machine Translation <br />
Location: Manhattan, NYC, NY<br />
* Deadline: Open until filled <br />
* Date posted: 6th November 2016<br />
* Contact: [mailto:Jia.Xu@hunter.cuny.edu Dr. Jia Xu]<br />
<br />
The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for one post-doctoral position. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.<br />
<br />
Applicants should hold by the time the appointment begins a PhD (or its equivalent) in Computer Science, Computer Engineering, Statistics, Mathematics, Physics or in a related discipline. We are seeking for applicants committed to either (1) extending their current research program in statistical Natural Language Processing or (2) employing their analytical and engineering skills and join in our current research program. Therefore, this position can be also seen as an opportunity to fast-forward develop statistical NLP skills and conduct cutting-edge research in this field.<br />
<br />
The position is for 1 year with the possibility of extending it up to 3 years. The starting date is flexible.<br />
<br />
The Hunter College at the City University of New York may ask the post-doctor to take up a very moderate teaching load (can be waived based on research promise). The salary commensurate with qualifications and research potential and starts from $50K/year.<br />
<br />
Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for collaboration. Hunter college is surrounded by top research labs (e.g. Google Research, Microsoft Research, Facebook, IBM Research), and many other university departments (e.g. Princeton, Columbia, NYU).<br />
<br />
Applications should include a recent CV and optionally a research statement and 2 representative publications. Applications should be sent to Dr. Jia Xu by email to: jia.xu@hunter.cuny.edu including in the Subject title the keyword: “Application”.<br />
<br />
All applicants will be notified upon receipt of the application by email.<br />
<br />
This position will be advertised at http://jiaxu.org until is filled.<br />
<br />
Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.<br />
<br />
<br />
<br />
== One fully funded PhD Position in Statistical Natural Language Processing in CUNY (at Manhattan, NYC) ==<br />
<br />
Employer: Department of Computer Science at Hunter College, University of New York<br />
Title: fully-funded PhD position<br />
Specialty: NLP<br />
* Location: Manhattan, NYC, NY<br />
* Deadline: Open until filled <br />
* Date posted: 6th November 2016<br />
* Contact: [mailto:Jia.Xu@hunter.cuny.edu Dr. Jia Xu]<br />
<br />
<br />
The Statistical Machine Learning and Translation group of Dr. Xu at the City University of New York is inviting applications for one fully-funded PhD student position starting in 2017. This is a splendid opportunity to conduct research blending very applied research (i.e. industrial-level Machine Translation systems) with foundational research in statistical machine learning. Dr. Xu’s group has an excellent record (e.g. winning first-place) in the international machine translation competitions during the last decade. The current research has evolved into exciting areas beyond statistical machine translation, such as in the foundations of machine learning and in frameworks in understanding the underlying geometry of languages.<br />
<br />
Applicants should hold by the time that begin their PhD studies a BSc, BEng (or its equivalent) in Computer Science, Linguistics, Computer Engineering, Statistics, Mathematics, Physics or related disciplines. We are seeking for very motivated students with enthusiasm and dedication in conducting cutting-edge research in statistical methods over massive amounts of data. Natural Language Processing is the prototypical domain where Machine Learning and Big Data are required to come together.<br />
<br />
The typical duration of the PhD program is from 3 to 4 years. <br />
<br />
The Hunter College at the City University of New York asks that the PhD candidate should take up two teaching assistantships per year. The admitted student will be offered to have the tuition fees covered and also stipend sufficient to cover the living cost.<br />
<br />
Hunter college is located in upper-east Manhattan. This is an extremely vibrant research location with numerous opportunities for internships and collaboration. Hunter college is surrounded by top research labs, such as Google Research, Microsoft Research, Facebook, and IBM Research.<br />
<br />
Application material: CV and optionally a statement of purpose letter, GRE, and TOELF/IELTS results. Applications should be sent to Dr. Jia Xu by email to: Jia.Xu@hunter.cuny.edu including in the Subject title the keyword: “PhD".<br />
<br />
All applicants will be notified upon receipt of the application by email.<br />
<br />
This position will be advertised at http://jiaxu.org until the position is filled.<br />
<br />
Hunter is committed to a policy of equal employment and equal access in its educational programs and activities. Diversity, inclusion, and an environment free from discrimination are central to the mission of the City University of New York.<br />
<br />
<br />
<br />
== Funded PhD Position in Natural Language Processing in Barcelona ==<br />
<br />
* Employer: Department of Information and Communication Technologies at Universitat Pompeu Fabra<br />
* Title: PhD studentship position<br />
* Specialty: NLP<br />
* Location: Barcelona, Spain<br />
* Deadline: August 8th, 2016 (or until filled) <br />
* Date posted: 29th July 2016<br />
* Contact: [mailto:horacio.saggion@upf.edu Prof. Horacio Saggion]<br />
<br />
<br />
The Department of Information and Communication Technologies at Universitat Pompeu Fabra in Barcelona, Spain, invites applications for a PhD studentship position that is associated with the María de Maeztu Units of Excellence Research Program of the Spanish Government (http://www.upf.edu/mdm-dtic), and involves joint work of the research labs of profs. Horacio Saggion and Ricardo Baeza-Yates. This position will be funded under the FPI call to be launched by the Spanish Ministry of Economy and Competitiveness.<br />
<br />
Project Description<br />
<br />
In the context of our Maria de Maeztu (MdM) project "Mining the Knowledge of Scientific Publications" ( see http://www.upf.edu/mdm-dtic) the PhD student will carry out a research project on the more focused area of automatic research paper assessment which concerns a number of interesting research questions including but not limited to: <br />
<br />
* automatic research paper evaluation<br />
* automatic research paper/author impact prediction<br />
* automatic novelty evaluation<br />
<br />
The PhD will benefit from the resources developed during MdM project: availability of large scale open scientific repositories, natural language processing technology adapted to scientific text processing, document retrieval technology, etc. as well as the expertise of the MdM team members.<br />
<br />
Applicants<br />
<br />
Candidates should hold a M.Sc. in Computer Science or related field with a solid background in Natural Language Processing and be proficient in spoken and written English. Experience with recent advances in Machine Learning and Information Retrieval would be highly valuable. Knowledge of statistical analysis is highly desirable.<br />
<br />
More information<br />
<br />
For informal inquiries, prospective candidates may contact professor Horacio Saggion at horacio DOT saggion AT upf DOT edu <br />
<br />
For more information please check the official announcement at <br />
<br />
https://portal.upf.edu/web/etic/automatic-research-assessment?p_p_id=56_INSTANCE_MaAxd6TFfhia&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&p_p_col_id=column-1&p_p_col_count=1<br />
<br />
== Research Fellow in Biomedical Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Fellow<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: August 13, 2016<br />
*Date posted: July 18, 2016<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a postdoctoral research fellow in Biomedical Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester.<br />
<br />
The objective of this BBSRC funded post in collaboration with Unilever is to conduct research into extracting complex information from the scientific literature to support metabolic pathway curation using text mining methods. <br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, etc., and in high quality journals; excellent programming skills; proven ability to develop independently research proposals. <br />
<br />
* Duration of post: until 31st March 2018 with possibility of extension<br />
* Salary: £38,896 to £47,801 per annum<br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems.<br />
NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
<br />
The project will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics.<br />
More information about the project: http://www.nactem.ac.uk/empathy/<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).<br />
<br />
Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=11856<br />
<br />
== Computational Linguist-Morphology ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist-Morphology<br />
* Specialty: Application of Finite State Transducers (FST) to language processing technologies, development of FST networks for languages, integration of morphological analyzers.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist-Morphology provides unique expertise with the application of FST to language processing technologies, to include the development of FST networks for languages, the integration of morphological analyzers in multilingual databases/search engines and the development of APIs for managing FST I/O in a multilingual environment.<br />
<br />
''Qualifications''<br />
<br />
*A master's degree in computer science and/or linguistics, or in a related field; eight (8) years related experience in FST technologies for language applications may be substituted for a master's degree.<br />
<br />
*Within the last ten (10) years, shall have a minimum of seven (7) years experience programming language networks in one or more FST applications such as XSFT, Stuttgart Finite State Transducer Toolkit, OpenFST, FOMA, or other product with equivalent functional capabilities.<br />
<br />
*Shall have a minimum of five (5) years experience coding with two (2) or more of the following: C, C++, or Java. Shall also have a minimum of five (5) years experience with Perl and/or Python scripting languages.<br />
<br />
*Within the last ten (10) years, shall have a minimum of five (5) years experience with linguistics and language structure, language processing technologies, and/or with applying morphologies to multilingual databases/search engines.<br />
<br />
*Shall have a minimum of five (5) years experience with two (2) or more foreign languages. Shall have demonstrated experience with international encodings, to include converting and handling multilingual encoding, such as UTF-8.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist-Morphology".<br />
<br />
== Computational Linguist ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist<br />
* Specialty: Integration of NLP Modules, Experimentation with User Interfaces for Analytic Support, Web Services for Querying Extracted Results.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist provides unique expertise with the application of computer science to language processing technologies, to include experimentation with, and integration of, unique NLP modules, experimentation with user interfaces for analytic support, web development, and development of web services for querying extracted results. <br />
<br />
''Qualifications''<br />
<br />
*MA in computer science and/or linguistics, or in a related field (8 years related experience may be substituted for a Master's Degree). <br />
<br />
*Within the last 10 years shall have a minimum of 7 years experience each programming: C, C++, or Java.<br />
<br />
*Within the last 5 years, shall have a minimum of 3 years programming with two or more scripting languages (e.g. Perl, Python).<br />
<br />
*Within the last 10 years, shall have a minimum of 5 years experience with linguistics and language structure, language processing technologies, and/or with applying ontologies to NLP applications. <br />
<br />
*A minimum of 5 years experience with two or more foreign languages is required. <br />
<br />
*Shall have demonstrated experience developing software in a Linux environment, with Semantic Web technologies (e.g. RDF, OWL), and with international encodings, to include converting and handling multilingual encoding, such as UTF - 8 is required.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist".<br />
<br />
== Research Associate/Fellow in Machine Learning, University of Sheffield, UK ==<br />
* Employer: [http://www.sheffield.ac.uk/ University of Sheffield], UK<br />
* Title: Research Associate/Fellow<br />
* Specialty: ML<br />
* Location: Sheffield<br />
* Deadline: July 18, 2016<br />
* Date posted: June 17, 2016<br />
* Contact: [mailto:l.specia@sheffield.ac.uk Prof. Lucia Specia]<br />
<br />
<br />
We have an opening for a 3-year position of Research Associate or Research Fellow in Machine Learning with applications to Machine Translation and Multimodal Language Processing. This position is funded by the ERC MultiMT project: Multi-modal Context Modelling for Machine Translation, led by Prof. Lucia Specia (www.dcs.shef.ac.uk/~lucia) at the University of Sheffield.<br />
<br />
This is a highly interdisciplinary project involving Natural Language Processing, Computer Vision and Machine Learning. Its goal is to devise methods and algorithms to exploit global multi-modal information for context modelling in Machine Translation. The post holder will be expected to investigate new ways to acquire multilingual multi-modal representations, and new machine learning and inference algorithms that can learn from these rich context models to generate high quality translations. In addition, if appointed as Research Fellow, the post holder will be expected to make significant contributions to multi-modal language processing in general, drawing from their experience in Computer Vision and Natural Language Processing.<br />
<br />
This is an opportunity to work in a well-connected international team with world-leading reputation in the Natural Language Processing (NLP) research group at the University of Sheffield. The NLP group is well known internationally for its research, and is one of the largest research groups in the area in Europe.<br />
<br />
This post offers excellent opportunities for publications, project visits and conference trips. Applicants should have (for Research Associate (RA) and Research Fellow (RF) posts):<br />
<br />
* PhD (or equivalent work experience) in Computer Science, Statistics, Mathematics or related areas<br />
* Significant experience and track record in Machine Learning (RA and RF)<br />
* Strong publication record commensurate with career stage (RA and RF)<br />
* Experience and strong track record in Computer Vision (desirable for RA, required for RF)<br />
* Experience and strong track record in Natural Language Processing (desirable for both RA and RF)<br />
* Strong programming experience, particularly in Python or C++. (RA and RF)<br />
<br />
This post is fixed-term with a start date from August 2016 (or soon after) and duration of ''3 years'' with possibility of extension to ''5 years''.<br />
<br />
'''Salary range''': £28,847 to £46,414 per annum.<br />
<br />
For informal inquiries contact Dr. Lucia Specia: L.Specia@sheffield.ac.uk<br />
<br />
For more information about the post and for '''applications''': http://www.shef.ac.uk/jobs, Search and apply for jobs using reference number UOS014018<br />
<br />
<br />
<br />
== Doctoral Researcher at UKP/KRITIS, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a '''Doctoral Researcher''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
'''Working environment and conditions:''' KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by '''10 July 2016'''. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11595Employment opportunities, postdoctoral positions, summer jobs2016-07-24T15:24:41Z<p>Tristan Miller: ssociate Research Scientist, UKP Lab, TU Darmstadt</p>
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<br />
== Associate Research Scientist, UKP Lab, TU Darmstadt ==<br />
<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Associate Research Scientist<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: August 31, 2016<br />
* Date posted: July 24, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab has an opening for an '''Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two years)''' to strengthen the group’s profile in the areas of (i) Unsupervised/Weakly Supervised NLP and its applications in semantic or discourse analysis,(ii) Computational Argumentation, or (iii) NLP methods to tackle novel problems in Social Sciences and Humanities. The UKP Lab is a research group at the Department of Computer Science at the Technische Universität Darmstadt, Germany. It comprises about 40 team members who work on various aspects of Natural Language Processing (NLP). The department was [http://csrankings.org/ recently ranked] among the top three in Europe in the area of NLP.<br />
<br />
We ask for applications from candidates in Computer Science, Computational Linguistics, or related fields, preferably with R&D project expertise, and strong communication skills in English and German. The successful applicant will work in projects including R&D activities in the areas listed above. Prior work in the respective fields is a definite advantage. Experience with deep learning is a strong plus. Ideally, the candidates should have demonstrable experience in designing and implementing NLP systems and algorithms in Java or Python, and experience in machine learning, information retrieval, and large-scale data processing. Combining fundamental NLP research in the above listed areas with applications from industry and social sciences and humanities will be highly encouraged. UKP Lab offers a supportive atmosphere and attractive opportunities for personal career development.<br />
<br />
UKP’s wide cooperation network, both within its own research community and with partners from industry and the social sciences and humanities, will provide a great environment for the successful applicant. The Department of Computer Science of TU Darmstadt is regularly ranked among the best in German universities. Its unique research initiative "Knowledge Discovery in the Web” and DFG-funded Research Training Group [https://www.aiphes.tu-darmstadt.de/de/aiphes/ “Adaptive Information Processing of Heterogeneous Content” (AIPHES)] emphasize NLP, text mining, and machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. The UKP Lab is a dynamic, high-profile research group committed to excellent research results, technologies of the highest industrial standards, a cooperative work style, and close interaction of team members working on joint projects.<br />
<br />
Applications should include a CV, a motivation letter, and an outline of previous working or research experience (if available). <br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send applications to [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31 August 2016. The position will remain open until filled. Interviews may start any time.<br />
<br />
<br />
== Research Fellow in Biomedical Text Mining, University of Manchester, UK ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Fellow<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: August 13, 2016<br />
*Date posted: July 18, 2016<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a postdoctoral research fellow in Biomedical Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester.<br />
<br />
The objective of this BBSRC funded post in collaboration with Unilever is to conduct research into extracting complex information from the scientific literature to support metabolic pathway curation using text mining methods. <br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, etc., and in high quality journals; excellent programming skills; proven ability to develop independently research proposals. <br />
<br />
* Duration of post: until 31st March 2018 with possibility of extension<br />
* Salary: £38,896 to £47,801 per annum<br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems.<br />
NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
<br />
The project will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics.<br />
More information about the project: http://www.nactem.ac.uk/empathy/<br />
<br />
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).<br />
<br />
Application form and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=11856<br />
<br />
== Computational Linguist-Morphology ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist-Morphology<br />
* Specialty: Application of Finite State Transducers (FST) to language processing technologies, development of FST networks for languages, integration of morphological analyzers.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist-Morphology provides unique expertise with the application of FST to language processing technologies, to include the development of FST networks for languages, the integration of morphological analyzers in multilingual databases/search engines and the development of APIs for managing FST I/O in a multilingual environment.<br />
<br />
''Qualifications''<br />
<br />
*A master's degree in computer science and/or linguistics, or in a related field; eight (8) years related experience in FST technologies for language applications may be substituted for a master's degree.<br />
<br />
*Within the last ten (10) years, shall have a minimum of seven (7) years experience programming language networks in one or more FST applications such as XSFT, Stuttgart Finite State Transducer Toolkit, OpenFST, FOMA, or other product with equivalent functional capabilities.<br />
<br />
*Shall have a minimum of five (5) years experience coding with two (2) or more of the following: C, C++, or Java. Shall also have a minimum of five (5) years experience with Perl and/or Python scripting languages.<br />
<br />
*Within the last ten (10) years, shall have a minimum of five (5) years experience with linguistics and language structure, language processing technologies, and/or with applying morphologies to multilingual databases/search engines.<br />
<br />
*Shall have a minimum of five (5) years experience with two (2) or more foreign languages. Shall have demonstrated experience with international encodings, to include converting and handling multilingual encoding, such as UTF-8.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist-Morphology".<br />
<br />
== Computational Linguist ==<br />
<br />
* Employer: [http://www.edcknowledge.com/ Esprit de Corps Corporation (EdC)], US<br />
* Title: Computational Linguist<br />
* Specialty: Integration of NLP Modules, Experimentation with User Interfaces for Analytic Support, Web Services for Querying Extracted Results.<br />
* Location: Various US Locations<br />
* Deadline: Open<br />
* Date posted: June 19, 2016<br />
* Contact: [mailto:jlay@edcknowledge.com. Jim Lay]<br />
<br />
<br />
EdC provides linguistic and cultural insight in support of US national interests. We are a woman owned, small business, and an equal opportunity employer.<br />
<br />
The Computational Linguist provides unique expertise with the application of computer science to language processing technologies, to include experimentation with, and integration of, unique NLP modules, experimentation with user interfaces for analytic support, web development, and development of web services for querying extracted results. <br />
<br />
''Qualifications''<br />
<br />
*MA in computer science and/or linguistics, or in a related field (8 years related experience may be substituted for a Master's Degree). <br />
<br />
*Within the last 10 years shall have a minimum of 7 years experience each programming: C, C++, or Java.<br />
<br />
*Within the last 5 years, shall have a minimum of 3 years programming with two or more scripting languages (e.g. Perl, Python).<br />
<br />
*Within the last 10 years, shall have a minimum of 5 years experience with linguistics and language structure, language processing technologies, and/or with applying ontologies to NLP applications. <br />
<br />
*A minimum of 5 years experience with two or more foreign languages is required. <br />
<br />
*Shall have demonstrated experience developing software in a Linux environment, with Semantic Web technologies (e.g. RDF, OWL), and with international encodings, to include converting and handling multilingual encoding, such as UTF - 8 is required.<br />
<br />
''Applicants must be United States citizens able to acquire a personal security clearance.''<br />
<br />
For more information about the post and for '''applications''': http://edcknowledge.com/join-the-corps-2/, Search and apply for the position titled "Computational Linguist".<br />
<br />
== Research Associate/Fellow in Machine Learning, University of Sheffield, UK ==<br />
* Employer: [http://www.sheffield.ac.uk/ University of Sheffield], UK<br />
* Title: Research Associate/Fellow<br />
* Specialty: ML<br />
* Location: Sheffield<br />
* Deadline: July 18, 2016<br />
* Date posted: June 17, 2016<br />
* Contact: [mailto:l.specia@sheffield.ac.uk Prof. Lucia Specia]<br />
<br />
<br />
We have an opening for a 3-year position of Research Associate or Research Fellow in Machine Learning with applications to Machine Translation and Multimodal Language Processing. This position is funded by the ERC MultiMT project: Multi-modal Context Modelling for Machine Translation, led by Prof. Lucia Specia (www.dcs.shef.ac.uk/~lucia) at the University of Sheffield.<br />
<br />
This is a highly interdisciplinary project involving Natural Language Processing, Computer Vision and Machine Learning. Its goal is to devise methods and algorithms to exploit global multi-modal information for context modelling in Machine Translation. The post holder will be expected to investigate new ways to acquire multilingual multi-modal representations, and new machine learning and inference algorithms that can learn from these rich context models to generate high quality translations. In addition, if appointed as Research Fellow, the post holder will be expected to make significant contributions to multi-modal language processing in general, drawing from their experience in Computer Vision and Natural Language Processing.<br />
<br />
This is an opportunity to work in a well-connected international team with world-leading reputation in the Natural Language Processing (NLP) research group at the University of Sheffield. The NLP group is well known internationally for its research, and is one of the largest research groups in the area in Europe.<br />
<br />
This post offers excellent opportunities for publications, project visits and conference trips. Applicants should have (for Research Associate (RA) and Research Fellow (RF) posts):<br />
<br />
* PhD (or equivalent work experience) in Computer Science, Statistics, Mathematics or related areas<br />
* Significant experience and track record in Machine Learning (RA and RF)<br />
* Strong publication record commensurate with career stage (RA and RF)<br />
* Experience and strong track record in Computer Vision (desirable for RA, required for RF)<br />
* Experience and strong track record in Natural Language Processing (desirable for both RA and RF)<br />
* Strong programming experience, particularly in Python or C++. (RA and RF)<br />
<br />
This post is fixed-term with a start date from August 2016 (or soon after) and duration of ''3 years'' with possibility of extension to ''5 years''.<br />
<br />
'''Salary range''': £28,847 to £46,414 per annum.<br />
<br />
For informal inquiries contact Dr. Lucia Specia: L.Specia@sheffield.ac.uk<br />
<br />
For more information about the post and for '''applications''': http://www.shef.ac.uk/jobs, Search and apply for jobs using reference number UOS014018<br />
<br />
<br />
<br />
== Doctoral Researcher at UKP/KRITIS, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a '''Doctoral Researcher''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
'''Working environment and conditions:''' KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by '''10 July 2016'''. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11529Employment opportunities, postdoctoral positions, summer jobs2016-06-10T20:52:24Z<p>Tristan Miller: /* Doctoral Researcher at UKP/KRITIS, TU Darmstadt */ formatting</p>
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<br />
== Doctoral Researcher at UKP/KRITIS, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a '''Doctoral Researcher''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
'''Working environment and conditions:''' KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by '''10 July 2016'''. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11528Employment opportunities, postdoctoral positions, summer jobs2016-06-10T20:51:12Z<p>Tristan Miller: update KRITIS listing</p>
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== Doctoral Researcher at UKP/KRITIS, TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking a '''Doctoral Researcher''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
Working environment and conditions: KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to Prof. Gurevych at [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by '''10 July 2016'''. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11527Employment opportunities, postdoctoral positions, summer jobs2016-06-10T14:24:27Z<p>Tristan Miller: 12 Doctoral Researcher Positions at TU Darmstadt</p>
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<br />
== 12 Doctoral Researcher Positions at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt<br />
* Deadline: July 10, 2016<br />
* Date posted: June 10, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] (for further information), [mailto:info@kritis.tu-darmstadt.de info@kritis.tu-darmstadt.de] (applications)<br />
<br />
KRITIS ("Kritische Infrastrukturen: Konstruktion, Funktionskrisen und Schutz in Städten"), a new interdisciplinary research training group at Technsiche Universität Darmstadt and funded through the German Research Foundation, is currently seeking '''12 Doctoral-track Research Scientists''' to start on 1 October 2016.<br />
<br />
KRITIS researches systems for technical supply and disposal, and for communication and transport, which have become the central nervous system of modern cities. Their disruption can trigger dramatic crises. Modern city infrastructures are increasingly vulnerable not only to external threats (natural disasters, terrorist attacks, and cyber attacks) but also due to their inherent complexity and interdependence. Our aim is to understand and describe these complex systems in their spatial and temporal contexts. This is done in three main research areas:<br />
<br />
# We want to ensure that technical infrastructures are constructed with the term "critical" in mind. We therefore ask what technical-functional needs, and political and social considerations, are relevant, and how these vary according to the systems' historical and spacial context.<br />
# We assume that the complex spatial and temporal arrangements become particularly visible during infrastructural-functional crises. We therefore investigate failures of urban infrastructures, including the conditions contributing to their vulnerability or resilience.<br />
# Finally, we ask how we can best organize protection against or preparation for infrastructural-functional crises (so-called "prevention and preparedness").<br />
<br />
Research in the training group takes an interdisciplinary approach, with cooperation among the following specialities: space and infrastructure planning, modern and contemporary history, medieval history, philosophy of technology, comparative analysis of political systems, ubiquitous knowledge processing, urban design and planning, rail systems, and computer science for architecture and construction.<br />
<br />
In this area, the discipline of ubiquitous knowledge processing (Prof. Iryna Gurevych) is concerned with the interactions between urban infrastructure (e.g., transport, telecommunications), communication in social media, and the relevant spatial and temporal analysis methods from the perspective of adaptive information and text processing. This will be of particular interest to doctoral candidates in the fields of real-time text analysis which can be applied to the early detection of crises, to public opinion-making, or to crisis management through automated evaluation of (online) content such as Twitter.<br />
<br />
Possible dissertation topics include:<br />
* Social-spatial differences of criticality: location- and class-specific text-analytic mining of argumentation on urban infrastructure in social media<br />
* Mining of arguments on urban infrastructure in social media for cascading reactions (i.e., spatio-temporal spread of social media responses to the collapse of urban infrastructure)<br />
* Early recognition of vulnerability: Real-time monitoring of information on hazards to urban infrastructure in social media<br />
* User expectations on the speed of resolution of infrastructural failures – comparison and analysis of tweets across national boundaries<br />
<br />
For discussion or advice on further possible research topics and organizational issues, please contact Prof. Iryna Gurevych [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de].<br />
<br />
'''Requirements:''' The successful applicants should produce a doctoral dissertation related to one or more of the above-noted research priorities. This dissertation should be completed within three years and submitted to one of the departments of Technische Universität Darmstadt. Further information on KRITIS's scientific program and its participating professors will be available soon on the following website: [http://www.kritis.tu-darmstadt.de http://www.kritis.tu-darmstadt.de]<br />
<br />
It is expected that all members of the research training group will be intensively engaged in interdisciplinary cooperation leading to scholarly publications and lectures. To this end, regular participation in seminars, symposia, workshops, etc. is required, which necessitates the doctoral candidates being domiciled in the Rhine-Main area.<br />
<br />
Working environment and conditions: KRITIS offers an excellent research infrastructure for doctoral students who wish to carry out their own research project within an innovative and internationally networked program. The members of the group work in shared offices under the support and patronage of participating professors. Among the special services include the possibility of a financed stay abroad in one of four internationally renowned partner universities. We also work with various partners in the private and public sector (companies, government offices, and other organizations) at which candidates can complete internships.<br />
<br />
Salaries for doctoral candidates depend on qualifications and experience, and will be in line with the collective agreement for employees at TU Darmstadt (TV-TU Darmstadt). The positions are limited to three years and include, depending on the field, 65% to 100% (full-time) employment.<br />
<br />
'''Your application:''' TU Darmstadt strives to increase its number of female employees, and as such particularly encourages women to apply. All other things being equal, applicants who have a degree of disability of at least 50% (or the equivalent) will receive preference. Please prepare your application in English or German, and compressed as a single file (up to 6 MB). Applications should be sent by e-mail to your prospective supervisor and also to [mailto:info@kritis.tu-darmstadt.de info@kritis.tu-darmstadt.de] by 10 July 2016. The application should include a CV listing language skills and overseas experience, scanned copies of academic credentials, and a sketch of up to five pages for a doctoral project.<br />
<br />
We look forward to receiving your application!<br />
<br />
== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11513Employment opportunities, postdoctoral positions, summer jobs2016-06-06T08:20:52Z<p>Tristan Miller: Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg</p>
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== Doctoral Researcher in NLP at TU Darmstadt and/or University of Heidelberg ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt] and/or [http://www.uni-heidelberg.de/ Ruprecht-Karls-University Heidelberg], Germany<br />
* Title: Doctoral researcher<br />
* Specialty: NLP<br />
* Location: Darmstadt and/or Heidelberg, Germany<br />
* Deadline: June 30, 2016<br />
* Date posted: June 6, 2016<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Research Training Group „Adaptive Information Preparation from Heterogeneous Sources“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht‑Karls‑University Heidelberg is filling a position for three years, starting as soon as possible: '''Doctoral Researcher in Natural Language Processing'''<br />
<br />
The position provides the opportunity to obtain a doctoral degree with an emphasis on the guiding theme D1: Multi-level models of information quality, under the leadership of Prof. Dr. Iryna Gurevych (UKP Lab, TU Darmstadt). A possible research focus of the position is an automatic claim checking with its applications in the domain of computational journalism. However, other suitable topics may be proposed as well. The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment are being developed. AIPHES investigates a novel scenario for information preparation from heterogeneous sources, within the application context of multi-document summarization. There exists close interaction with end users who prepare textual documents in an online editorial office and therefore profit from the results of AIPHES. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler, Dr. Meyer), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann). Participants at the Ruprecht‑Karls‑University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES emphasizes close contact between students and their advisors, has regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and actively supports its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Prerequisites'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht‑Karls‑University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. <br />
<br />
Applications should include: <br />
<br />
* a motivational letter explaining the applicant’s possible contribution to the guiding theme D1,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
<br />
They should be submitted until June 30th, 2016 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]. <br />
<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11508Employment opportunities, postdoctoral positions, summer jobs2016-06-01T16:12:18Z<p>Tristan Miller: Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt</p>
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<br />
== Full Professor (W3) for Real-Time Data Analytics at TU Darmstadt ==<br />
<br />
* Employer: [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany<br />
* Title: Full Professor<br />
* Specialty: Real-Time Data Analytics, with interdisciplinary experience in NLP<br />
* Location: Darmstadt, Germany<br />
* Deadline: July 6, 2016<br />
* Date posted: June 1, 2016<br />
* Contact: [mailto:dekanat@informatik.tu-darmstadt.de dekanat@informatik.tu-darmstadt.de] (for applications); [mailto:gurevych@ukp.informatik.tu-darmstadt.de Iryna Gurevych] (for further information)<br />
<br />
The Department of Computer Science at Technische Universität Darmstadt invites applications for the position of '''Full Professor (W3) for Real-Time Data Analytics''' to be appointed as soon as possible.<br />
<br />
We are seeking an outstanding researcher to establish the Department’s new area of real-time data analytics through research and teaching. The main focus of the professorship will be on excellent, method-oriented research, with close links to systems and applications. It is also expected that the successful candidate plays a formative role in cross-department and interdisciplinary research activities; the bridge to engineering departments of the university, in particular to the department of mechanical engineering, is particularly important in this respect. <br />
<br />
Relevant topics include real-time data analytics on dynamic data streams of various types (including sensor data, text, and images), adaptive information processing and integration, and interactive machine learning. Further topics of research include data analysis and its applications in the mining of data and data streams of heterogeneous nature, quality, and quantity and in the support of decision-making processes, decision management, and the creation of self-organizing systems. Example application areas include automotive engineering, transport and logistics, and cognitive information processing for information validation on the Web.<br />
<br />
We expect applicants to have interdisciplinary experience in the use of data analysis methods in cooperation with scientists from other fields as well as with industrial partners. The professorship is intended to strengthen those profile areas of TU Darmstadt in which real-time requirements and interactivity play a central role, such as the Internet and digitization and their associated research fields such as data science, Industry 4.0, autonomous driving, smart transport and energy networks, smart buildings, but also '''natural language processing''', cognitive science, and cybersecurity.<br />
<br />
In addition to an outstanding academic CV, applicants must demonstrate a strong commitment to teaching computer science (incl. foundational courses) at the Bachelor’s and Master’s levels. A willingness to participate in academic self-administration is also expected.<br />
<br />
Technische Universität Darmstadt is an autonomous university with a wide-ranging excellence in research, an interdisciplinary profile, and a strong focus on engineering as well as on information and communication technologies. Our Department is one of the leading national Computer Science departments and regularly ranked in the top group in national rankings.<br />
<br />
Employment will be on a non-tariff basis, with qualification-based compensation based on the German W-level salary. Applicants who are already professors classed as German civil servants (''Beamter'') can retain this status. Employment regulations from §§61 and 62 of the ''Hessisches Hochschulgesetz'' apply.<br />
<br />
Technische Universität Darmstadt is committed to increase the proportion of female scientific staff and therefore particularly encourages women to apply. All other things being equal, we will give preference to candidates with a degree of disability of at least 50 (or the equivalent).<br />
<br />
Applications, including all the usual supporting documents, should be submitted to the Dean of the Department of Computer Science, Technische Universität Darmstadt, Hochschulstr. 10, 64289 Darmstadt, Germany, e-mail dekanat@informatik.tu-darmstadt.de. Please quote '''reference No. 244'''.<br />
<br />
For further information, please contact Prof. Dr. Iryna Gurevych, tel. [+49] (0)6151 16 25290, gurevych@ukp.informatik.tu-darmstadt.de<br />
<br />
<br />
==NLP Postdoctoral Researcher at UNSW, Australia==<br />
<br />
* Employer: The University of New South Wales, Australia<br />
* Title: Research Associate/Fellow<br />
* Specialty: NLP, Knowledge Graph<br />
* Location: Sydney, Australia<br />
* Deadline: June 6th, 2016<br />
* Date posted: May 14th, 2016<br />
* Contact: Wei Wang (weiw@cse.unsw.edu.au)<br />
<br />
'''POSITION DESCRIPTION'''<br />
<br />
A postdoctoral position is available in School of Computer Science and<br />
Engineering at the University of New South Wales, Australia. The successful<br />
candidate will work with Dr. Wei Wang on utilizing Natural language processing<br />
(NLP), data mining, and semantic web to develop novel algorithms, tools and<br />
methods for constructing and maintaining domain-specific knowledge graphs from<br />
vast amount of unstructured/semi-structured data sources. This position is<br />
funded by Data to Decisions Cooperative Research Centre (D2D CRC), which was<br />
established in 2014 with a grant of A$25 million from the Australian Government,<br />
researchers and industry to provide the Big Data capability resulting in a safer<br />
and more secure nation and a sustainable Big Data workforce for Australia.<br />
<br />
<br />
'''POSITION REQUIREMENTS'''<br />
<br />
Essential criteria:<br />
<br />
* Proven ability to undertake research in a relevant research area (e.g. natural language processing, data mining, knowledge graph) at an international level, as evidenced by research output.<br />
* Excellent programming skills (java or C/C++).<br />
* A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, KDD, IJCAI, AAAI, ICML, NIPS, SIGMOD, VLDB) and journals.<br />
* Proven ability to communicate specialist ideas clearly in English using written media.<br />
* Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.<br />
* A PhD in Computer Science or closely related area, or equivalent experience. Candidates with pending degrees who will successfully defend their dissertations by August 1, 2016 will also be considered.<br />
<br />
<br />
Desirable criteria:<br />
<br />
* Knowledge of statistical natural language processing.<br />
* Knowledge of knowledge graph construction and applications.<br />
* Experience with analysing large text corpora using a high-performance computing environment.<br />
* Experience with python/R<br />
<br />
<br />
'''SALARY RANGE AND CONTRACT LENGTH'''<br />
<br />
* Research Associate: A$86,438 - A$92,453 per year (plus employer superannuation)<br />
* Research Fellow: A$97,090 - A$114,454 per year (plus employer superannuation)<br />
<br />
This is a fixed term position of one year with further renewal up to January 2019, subject to funding.<br />
<br />
<br />
'''ENVIRONMENT'''<br />
<br />
The School of Computer Science and Engineering in UNSW, located in Sydney, is<br />
one of the largest and leading computing schools in Australia. It offers both<br />
undergraduate and postgraduate programs in Software Engineering, Computer<br />
Engineering, Computer Science and Bioinformatics, as well as a number of<br />
combined degrees with other disciplines. It attracts excellent students who have<br />
an outstanding record in international competitions (such as Robocup).<br />
<br />
<br />
'''APPLICATION'''<br />
<br />
Please send a statement of interest, an academic CV (in pdf format) to Wei Wang<br />
(weiw@cse.unsw.edu.au) with the subject line starting with "[CRCPostdoc]". For<br />
informal queries, please send an email to weiw@cse.unsw.edu.au.<br />
<br />
<br />
<br />
<br />
<br />
<br />
==Computer Science Postdoctoral Researcher in Natural Language Processing for Social Science==<br />
<br />
* Employer: University of Pennsylvania<br />
* Title: Postdoctoral Researcher <br />
* Specialty: NLP<br />
* Location: Philadelphia, PA<br />
* Deadline: May 15th, 2016<br />
* Date posted: April 26th, 2016<br />
* Contact: Professor Lyle Ungar: ungar@cis.upenn.edu<br />
<br />
'''Summary'''<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression. <br />
The primary responsibility will, of course, be producing top-quality published research in areas of interest to you and the WWBP team. You will be expected to lead multiple peer-reviewed publications each year and to support (as secondary author and technical expert) many more publications. As part of that latter process, we would like you to serve as the equivalent of a “Chief Technology Officer” of the WWBP, providing technical oversight and mentoring to the programmers and data scientists who build and maintain our software and hardware infrastructure, and who do the vast bulk of the data collection and analysis for the WWBP. <br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. They will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwp.org for example publications.<br />
<br />
<br />
Approximate Start Date: Summer 2016<br />
<br />
<br />
'''How to Apply'''<br />
<br />
Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line. <br />
<br />
<br />
<br />
<br />
==Research Scientist, Natural Language Processing==<br />
<br />
* Employer: EMR.AI Inc.<br />
* Title: Research Scientist<br />
* Specialty: NLP<br />
* Location: San Francisco, CA<br />
* Deadline: May 20th, 2016<br />
* Date posted: April 21th, 2016<br />
* Contact: David Suendermann-Oeft ([mailto:david@emr.ai david@emr.ai])<br />
<br />
Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.<br />
<br />
'''Summary'''<br />
<br />
EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others.<br />
<br />
This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.<br />
<br />
'''Responsibilities'''<br />
<br />
* Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.<br />
* Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.<br />
* Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.<br />
* Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.<br />
* Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.<br />
<br />
'''Skills'''<br />
<br />
PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.<br />
<br />
'''Benefits'''<br />
<br />
EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.<br />
<br />
'''How to Apply'''<br />
<br />
Please send your application documents to [mailto:jobs@emr.ai jobs@emr.ai]<br />
<br />
'''Contact'''<br />
<br />
EMR.AI Inc.<br />
<br />
90 New Montgomery St<br />
<br />
San Francisco, CA 94105, USA<br />
<br />
phone: +1-415-200-8535<br />
<br />
e-mail: [mailto:info@emr.ai info@emr.ai]<br />
<br />
www: [http://emr.ai http://emr.ai]<br />
<br />
<br />
<br />
==Research Scientist on Natural Language Processing==<br />
<br />
* Employer: IBM Research Ireland<br />
* Title: Research Scientist<br />
* Specialty: NLP, Machine Learning<br />
* Location: Dublin<br />
* Deadline: May 5th, 2016<br />
* Date posted: April 11th, 2016<br />
* Contact: [https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?PageType=JobDetails&partnerid=26059&siteid=5016&AReq=36957BR link to application page]<br />
<br />
<br />
Ireland is accepting applications for full-time researchers in the area of natural language processing. The ideal candidate will have a PhD degree in computational linguistics or in computer science with a specialisation in Natural Language Processing (NLP). Prior experience in the area of text analytics with information extraction, information retrieval and machine learning are highly desirable, and experience with corpus linguistics or natural language understanding are a plus. Strong programming skills in Java are required.<br />
<br />
The successful research candidate must have demonstrated ability to define research plans, carry out leading research, and publish research results through professional journals, academic conferences, and patents.<br />
As a researcher you will be expected to organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions have a significant impact.<br />
<br />
<br />
==Postdoc Researcher on Vision and Language==<br />
<br />
* Employer: University of Liverpool<br />
* Title: Postdoc<br />
* Specialty: Computer Vision with an interest in human vision/language behaviour<br />
* Location: Liverpool UK<br />
* Deadline: April 20th, 2016<br />
* Date posted: March 28, 2016<br />
* Contact: [https://www.liverpool.ac.uk/working/jobvacancies/currentvacancies/research/r-590571/ link to application page]<br />
<br />
Applications are invited for a Postdoctoral Research associate position to study the relationship between visual/spatial representations and language. Language is often used to describe the visual world and this is done by labelling objects in the world with various categories such as roles (e.g., agent, goal). There is now a large infant social cognition literature which shows how categories like agents and goals may be identified using simple visual heuristics. In this post, we will strengthen these links by experimentally manipulating visual cues to see how they influence language choices in adults and children. In addition to the experimental study of these links, we will also develop computational models that use computer vision techniques to track the interaction of objects in videos and link these visual codes to the descriptions of the actions. We are most interested in people with a computational background who have an interest in human vision/language processing.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the ESRC International Centre for Language and Communicative Development (LUCID, http://www.lucid.ac.uk/), a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster. You should have (or be about to obtain) a PhD in the field related to Computer Science, Psychology, Cognitive Science, or related disciple. The post is available for 3 years.<br />
<br />
<br />
==Postdoc Positions at Johns Hopkins University==<br />
<br />
* Employer: Johns Hopkins University<br />
* Title: Postdoc<br />
* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine<br />
* Location: Baltimore, MD<br />
* Deadline: March 31, 2016<br />
* Date posted: March 1, 2016<br />
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]<br />
<br />
The Center for Language and Speech Processing (CLSP) at the Johns Hopkins University seeks applicants for postdoctoral fellowship positions in speech and language processing, including the areas of natural language processing, machine learning and health informatics. Applicants must have a Ph.D. in a relevant discipline and a strong research record.<br />
<br />
The center has a number of postdoctoral positions available for the coming year. Possible research topics include:<br />
* Trend Detection in Social Media<br />
* Broadly Multilingual Learning of Morphology<br />
* Stochastic approximation algorithms for subspace and multi-view representation learning<br />
* Analysis of large-scale time series data in healthcare<br />
<br />
Host faculty include:<br />
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria<br />
<br />
<br />
==Associate/Full Professor in Computational Linguistics at Stony Brook University==<br />
* Employer: Department of Linguistics, Stony Brook University<br />
* Title: Associate/Full Professor<br />
* Specialty: Computational Linguistics<br />
* Location: New York, USA<br />
* Deadline: <strike>March 14, 2016</strike> May 1, 2016<br />
* Date posted: February 17, 2015<br />
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]<br />
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]<br />
<br />
'''Job Description'''<br />
<br />
The Department of Linguistics at Stony Brook University invites applications for a tenured appointment in computational linguistics, beginning Fall 2016 or Fall 2017. This is a senior appointment at the Associate or Full Professor level.<br />
<br />
The successful candidate will have a PhD (preferably in Linguistics or Computer Science), an outstanding research profile in Computational Linguistics (ideally in areas that complement existing departmental strengths), a strong track record in grant acquisition, and teaching and advising experience at the graduate and/or undergraduate levels.<br />
<br />
They will also be expected to<br />
<br />
* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,<br />
* Initiate new collaborations and expand existing ones with other computational research groups on campus, in particular in the Department of Computer Science and the Institute for Advanced Computational Science,<br />
* Strengthen the department's connections with the local IT industry.<br />
<br />
Salary will be commensurate with education and experience.<br />
<br />
'''Application'''<br />
<br />
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]<br />
<br />
<br />
==Research Scientist at the Allen Institute for Artificial Intelligence==<br />
<br />
* Employer: Allen Institute for Artificial Intelligence (AI2)<br />
* Title: Research Scientist<br />
* Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
* Location: Seattle, WA<br />
* Deadline: N/A, we are hiring throughout 2016<br />
* Date posted: 02/09/2016<br />
* Contact information: ai2-info@allenai.org<br />
* Website: http://allenai.org/jobs.html<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
<br />
* Language and Vision<br />
* Information extraction and semantic parsing<br />
* Question answering<br />
* Language and reasoning<br />
* Machine learning and theory formation<br />
* Semantic search<br />
* Natural language processing<br />
* Diagram understanding<br />
* Visual knowledge extraction and visual reasoning<br />
<br />
And more…. <br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting AI2’s research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations. <br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, computer vision and machine learning, or question answering and explanation. We look favorably upon extensive work experience and publishing demonstrating application of your research. <br />
<br />
'''Why AI2'''<br />
<br />
In addition to AI2’s core mission of being a leader in the field of AI research, we also aim to create a superb team environment and to invest in each team member’s personal development. Some highlights are:<br />
<br />
* We are a learning organization – because everything AI2 does is ground-breaking, we are learning every day. Similarly, through weekly AI2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, AI2 is a place where you will have opportunities to continue learning right alongside us;<br />
* We value diversity of thought – we seek Research Scientists who can bring novel experiences and modes of problem solving to our leading-edge mission. If you are creative and efficient in your approach and insightful in your questioning, AI2 could be a great environment for you;<br />
* We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave;<br />
* We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures;<br />
* We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, we have the defending Super Bowl champions, and we have so much else. We even have kayaks for you to paddle right outside our front door;<br />
* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!<br />
<br />
'''Application Process'''<br />
<br />
Visit our website for more information: http://allenai.org/jobs.html<br />
<br />
<br />
==Software Engineer - Machine Learning / NLP (Chinese) at SYSTRAN==<br />
<br />
* Employer: SYSTRAN<br />
* Title: Software Engineer<br />
* Topics: Machine Learning, Natural Language Processing, Machine Translation<br />
* Location: San Diego<br />
* Deadline: Open until filled<br />
* Date Posted: January 29, 2016<br />
* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na<br />
<br />
SYSTRAN is currently seeking an experienced Software Engineer specializing in Machine Learning / NLP to join our R&D team in San Diego to develop machine translation systems.<br />
<br />
The ideal candidate must have a combination of research and implementation skills, including significant programming experience. Hands-on experience with machine learning, including deep neural network, text classification, statistical techniques for NLP or a related field, is highly desirable.<br />
<br />
Responsibilities include software development, experimentation, analysis of results, and building systems that combine linguistics and statistical language models for machine translation centering on Chinese language.<br />
<br />
'''Key Qualifications'''<br />
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology<br />
* Good algorithmic knowledge of machine learning<br />
* Experience writing and debugging software<br />
* Strong communications skills<br />
* Ability to work well as part of a team<br />
* Fluent in English.<br />
* Fluent in Chinese is a plus<br />
<br />
'''Education and Experience'''<br />
* MS or Ph D in Computational Linguistics / Computer Science or relevant field.<br />
* 2+ years work experience preferred<br />
<br />
'''Benefits'''<br />
* Successful candidates will be offered a competitive salary based on their qualifications and experience.<br />
<br />
<br />
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==<br />
<br />
* Employer: University of Dundee<br />
* Title: Lecturer/Senior Lecturer/Reader<br />
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence<br />
* Location: Dundee, UK<br />
* Deadline: 27 February 2016<br />
* Date Posted: 12 January 2016<br />
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)<br />
<br />
£34,576 to £55,389 Full Time, Permanent<br />
<br />
The University of Dundee’s School of Science & Engineering is advertising several permanent posts including one covering the Centre for Argument Technology. We are particularly keen to receive applications from candidates in Computational Linguistics to expand the group’s research in Argument Mining (see http://argmining2016.arg.tech and http://arg.tech/am), but welcome applications in all areas of the overlap between argumentation and artificial intelligence. A strong publication profile is essential, and for more senior appointments, so is a track record of funding success.<br />
<br />
For further information about the Centre for Argument Technology, please see http://arg.tech or contact Prof. Chris Reed; for more information about the position, see http://arg.tech/lecturer. General details follow.<br />
<br />
'''Summary of Job Purpose and Principal Duties'''<br />
<br />
The University of Dundee is seeking an exceptional candidate to join one of our Computing research groups, based within the School of Science and Engineering. The successful candidate will develop new research lines within either the (i) Human Centred Computing Group; (ii) the Centre for Argument Technology; or (iii) the Space Technology Centre. Full information on the current research in each<br />
group can be found in the Further Particulars.<br />
<br />
The successful candidate is expected to have a strong track record of research and a clear research plan that articulates with (or expands significantly) one of these areas. They will be expected to contribute to the development of research in this area by publishing in the highest quality journals and attracting appropriate research funding. For appointments at Grade 8 and 9, candidates are expected to show evidence of having attracted independent funding. The School encourages applications from holders of personal<br />
Fellowships.<br />
<br />
Additionally, the successful candidate will be expected to take an active role in the teaching of undergraduate computing programmes as well as supporting teaching at Masters level.<br />
<br />
'''Job Summary'''<br />
<br />
The appointee will be expected to contribute to research in Computing and to teaching and administration within the School of Science and Engineering. They will be expected to:<br />
<br />
* Contribute to the ongoing research in one of the three research groups described above.<br />
* Contribute to the generation of external research funding.<br />
* Publish in high quality research journals and major international conferences.<br />
* Teach at undergraduate and post-graduate level.<br />
* Supervise students at all levels (honours and MSc projects, PhD).<br />
* Undertake administrative duties.<br />
<br />
'''Application Requirements'''<br />
<br />
In addition to the online form, applicants must include with their application:<br />
<br />
* Cover letter outlining fit to role.<br />
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.<br />
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.<br />
<br />
<br />
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==<br />
* Employer: US Naval Research Laboratory<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence<br />
* Location: Washington, DC<br />
* Deadline: Open until filled<br />
* Date Posted: January 20, 2016<br />
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)<br />
<br />
'''Research focus''': The Postdoctoral Fellow will collaborate on various projects in reasoning, including (but not limited to) building a unified computational framework of reasoning; investigating how people engage in explanatory reasoning; and testing a system that reasons about time and temporal relations.<br />
<br />
'''Supervisor''': Sunny Khemlani, PhD<br />
<br />
'''Key qualifications''': A Ph.D. in cognitive psychology, cognitive science, or computer science, with experience in higher level cognition, experimental design and data analysis, or cognitive modeling. Experience with theories of reasoning, computer programming, and cognitive modeling is a strong plus.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.<br />
<br />
'''Program and compensation''': The Fellowship operates through the NRC Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). Only US citizenship or green card holders are eligible for the program. Fellows are compensated through a research stipend of ~$75,000/year.<br />
<br />
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.<br />
<br />
<br />
==Internship positions available at Juji, Inc.==<br />
* Employer: Juji, Inc.<br />
* Title: Intern<br />
* Location: Saratoga, CA<br />
* Deadline: open until all the positions are filled<br />
* Date Posted: January 14, 2016<br />
<br />
'''Description''': <br />
Have you ever watched the movie Her? Have you ever wondered or wished to have a virtual partner just like Samantha, who could tell you what you really are, whom your best partner may be, and even cheers you up? At Juji, we are building a hyper-personalized, virtual REP (Responsible, Empathetic Pal) for everyone. Your REP not only understands who you are, including your personality, motivations, and strengths, but it can also chat with you to learn and help fulfill your certain needs. <br />
<br />
We are seeking highly motivated and talented students, who are eager to help us tackle great technical challenges at Juji and to expand their knowledge and skills in the real world. We are especially interested in students who have had worked or love to work in the following areas: Artificial Intelligence, Natural Language Processing/Natural Language Generation, Machine Learning, Human-Computer Interaction, Information Visualization/Visual Analytics, and Cognitive Science.<br />
<br />
We have multiple positions on two main tracks:<br />
<br />
* Software development. If you love to create amazing software technologies and systems for real users, this is the track for you. You are expected to own and deliver a relatively independent project that will contribute to our cutting-edge product development effort.<br />
<br />
* Scientific research. If you love to design and conduct scientific experiments to answer a specific set of research questions, this is the track for you. You will work on a government funded research project on understanding human trust in a digital environment. You are expected to play a critical role in designing and conducting novel research studies and writing papers that lead to scientific publications.<br />
<br />
'''Qualifications'''<br />
Outstanding current students towards a bachelor or higher degree in the area of Computer Science, Computer Engineering, or equivalent disciplines are encouraged to apply. Strong software development or visual design skills are a plus. <br />
<br />
'''To apply''': Please email a copy of your resume to the following address: jobs@juji-inc.com with a subject line “Summer Internship 2016”, and state your track preference in your email body. <br />
<br />
<br />
<br />
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: January 8, 2016<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of high-dimensional predictive models in medicine. The models will be based on data from a large integrated healthcare system and will utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': experience with natural language processing; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills; strong programming and system development skills. Experience with artificial intelligence technologies, predictive modeling, Big Data and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': Immediately.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Employment_opportunities,_postdoctoral_positions,_summer_jobs&diff=11336Employment opportunities, postdoctoral positions, summer jobs2015-12-23T11:06:50Z<p>Tristan Miller: Associate Research Scientist at UKP Lab, TU Darmstadt</p>
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== Associate Research Scientist at UKP Lab, TU Darmstadt ==<br />
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], Department of Computer Science, Technische Universität Darmstadt<br />
* Title: Associate Research Scientist<br />
* Speciality: Natural Language Processing<br />
* Location: Darmstadt, Germany<br />
* Deadline: January 15, 2016<br />
* Date posted: December 23, 2015<br />
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]<br />
<br />
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for an '''Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two years)''' to strengthen the group's profile in the area of Computational Argumentation. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Computational Argumentation is one of the rapidly developing focus areas in collaboration with industrial partners.<br />
<br />
We ask for applications from candidates in Computer Science, Information Systems, Business Information Technology, or Computational Linguistics, preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of computational argumentation (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and experience in information retrieval, large-scale data processing and machine learning. In particular, experience with deep-learning is a strong plus. Combining fundamental NLP research on Computational Argumentation with industrial applications from different application domains will be highly encouraged.<br />
<br />
UKP's wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web" and the recently established Research Training Group "Adaptive Information Processing of Heterogeneous Content" (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.<br />
<br />
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).<br />
<br />
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 15 January 2016. The position is open until filled. Later applications may be considered if the position is still open.<br />
<br />
== Postdoctoral Researcher position in NLP/Computational Social Science at UPenn ==<br />
* Employer: Computer & Information Science, University of Pennsylvania, USA<br />
* Title: Postdoctoral Researcher<br />
* Speciality: Natural Language Processing, Computational Social Science<br />
* Location: Philadelphia, USA<br />
* Deadline: January 15, 2016<br />
* Date posted: December 21, 2015<br />
* Contact: applications@wwbp.org<br />
<br />
We invite applicants for a postdoctoral research position in natural language processing for health and social science, working on an interdisciplinary research project studying subjective well-being and health outcomes. The researcher will help develop state-of-the-art methods and models to better understand people, such as predicting personality from the words they use and automatically recognizing cognitive distortions typical of people prone to depression.<br />
<br />
The ideal candidate will have research experience in computational linguistics and applied machine learning. She or he will develop and code novel methods to leverage large datasets (i.e. billions of tweets) and use them to further our understanding of health, well-being, and the psychological states of individuals and large populations. Methods and results will be published in high impact computer science venues and, via collaboration with psychologists and medical doctors, in social science and health venues. See wwbp.org for example publications.<br />
<br />
* Application Deadline: January 15, 2015<br />
* Approximate Start Date: March 1, 2016 (but flexible)<br />
<br />
How to Apply: Send a detailed CV with at least 2 references who can be contacted for letters to applications@wwbp.org. Include job-code “POSTDOC-CS” in subject line.<br />
<br />
The University of Pennsylvania is an EOE/Affirmative Action Employer. Position contingent on funding.<br />
<br />
Primary Contact: Professor Lyle Ungar, ungar@cis.upenn.edu<br />
<br />
<br />
== Multiple positions as Full-time researcher, Post-doc researcher, Software Engineer and Summer Intern in IBM Research - Almaden, San Jose ==<br />
* Employer: IBM Research - Almaden<br />
* Title: Researcher, Software Engineer, Post-doc, Summer Intern<br />
* Speciality: natural language processing, information integration, entity resolution, machine learning, ontologies, and large-scale data management<br />
* Location: San Jose, CA<br />
* Deadline: (until filled)<br />
* Date posted: December 18, 2015<br />
* Contact: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
<br />
IBM Research - Almaden is looking for researchers to join the Natural Language Processing, Entity Resolution and Discovery Department. Our research focuses around creating a knowledge engineering platform for the creation, maintenance and consumption of “industry-specific” knowledge bases from a large number of (un/semi)structured public, licensed and enterprise content sources. Such a platform needs to support the entire lifecycle for knowledge engineering including:<br />
* creation, maintenance and evolution of ontologies to capture domain concepts of interest<br />
* scalable systems, tools and methodologies to support the development of individual analytic stages involved in creating knowledge from multiple sources such as text analytics, entity resolution and integration, cleansing, data transformations and machine learning; supporting domain adaptability and easy-to-use interfaces for key user personae for the individual analytic stages<br />
* scalable content services infrastructure that enables production-level deployment of these analytic workflows with support for continuous monitoring, introspection and recovery in the knowledge base creation process<br />
* techniques and methods for scalable and flexible indexing and querying support over the knowledge base supporting structured and search style queries, entity queries, as well as ad-hoc and exploratory queries<br />
* easy-to-use knowledge consumption interfaces for both human and machine consumption including support for discovery and ad-hoc NLQ driven interfaces<br />
* incorporating crowd sourcing and continuous evolution of the system through learning from user interactions. <br />
<br />
<br />
The research builds upon and extends successful projects from our group, which have resulted in academic, industrial and open source impact:<br />
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264<br />
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171<br />
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174<br />
<br />
<br />
The research is being conducted in close collaboration with the IBM Watson Solutions division and multiple global IBM Research labs (India, Haifa and Zurich), with focus around demonstrating scalable knowledge base construction in multiple industry domains (e.g., Healthcare, Financial and consumer domains).<br />
We are currently looking for researchers (Research Staff Members, software engineers, post-doc researchers and summer interns) with interest & experience in one or more areas relevant to the knowledge engineering life cycle such as natural language processing, information integration, entity resolution, machine learning, ontologies, and large-scale data management, as described above. <br />
<br />
<br />
Please send your resumes to: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)<br />
<br />
== Two Postdoc Opportunities at the US Army Research Lab in the Washington, DC Metro Area ==<br />
* Employer: US Army Research Laboratory<br />
* Title: Postdoctoral Fellow<br />
* Speciality: Knowledge Representation, Knowledge Bases, Common-Sense Reasoning, Planning<br />
* Location: Adelphi, MD<br />
* Deadline: (until filled)<br />
* Date posted: November 30, 2015<br />
* Contact: douglas.a.summers-stay.civ@mail.mil and/or ethan.a.stump2.civ@mail.mil<br />
<br />
The US Army Research Laboratory currently has two postdoc opportunities:<br />
<br />
<br />
'''Position #1'''<br />
<br />
The US Army Research Laboratory (ARL) is researching common-sense reasoning and natural language understanding for the purpose of creating a communication dialogue to promote increased intent understanding within Human-Robot teams. In support of this effort, ARL is looking for an individual with a PhD or equivalent, with interest and a background in knowledge representation, knowledge bases, knowledge graphs, common-sense reasoning, or spatial reasoning. We plan to make use of semantic vector spaces to enhance the capabilities of the reasoning system, so some familiarity with knowledge graph embedding, distributional semantic vector spaces (such as GloVe or word2vec), or learning from massive text corpora would also be beneficial.<br />
<br />
The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.<br />
<br />
To learn more about the position, or to apply, please send questions or a CV to Dr. Douglas Summers-Stay via email at douglas.a.summers-stay.civ@mail.mil.<br />
<br />
<br />
'''Position #2'''<br />
<br />
The US Army Research Laboratory (ARL) is seeking a Postdoctoral Researcher to bridge the gap between humans and autonomous systems by developing a controlled language to reason and communicate about human intent as it applies to commands a robot receives. In robotics, practitioners often program autonomous systems by developing monolithic behaviors that, when correctly parameterized, will cause the system to act as desired. However, setting these parameters is often more art than science, and we cannot expect an average user to effectively task the system unless they have only the simplest tasks in mind. ARL desires a controlled language that both concisely describes the capabilities of autonomous systems, as well as enables common-sense reasoning and representation of implicit goals that will let the system fill instructional gaps from novice users.<br />
<br />
In this position, the Researcher will work on a cross-disciplinary team comprised of researchers in computational linguistics, computer vision, machine learning, and experimental robotics to develop a system for interacting with humans—the goal being to develop and evolve complex plans carried out by autonomous systems. The primary responsibilities of the Researcher will be learning how we can use language to link the domains of intent reasoning and action, and developing such a language to enable experiments with humans and robot teams operating in dynamic environments.<br />
<br />
The candidate must have a PhD or equivalent degree, and should have an interest and background in formal methods, knowledge representation and reasoning, computational linguistics, control policies, or AI planning.<br />
<br />
The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.<br />
<br />
To learn more about the position, or to apply, please send questions or a CV to Dr. Ethan Stump via email at ethan.a.stump2.civ@mail.mil.<br />
<br />
<br />
== Open PhD position on Textual Knowledge Resources (NLP / IR / ML) at Data and Web Science Group in Mannheim, Germany ==<br />
* Employer: The Data and Web Science Research Group, University of Mannheim, Germany<br />
* Title: PhD Candidate (post-Masters)<br />
* Speciality: Natural Language Processing, Information Retrieval, Knowledge Bases<br />
* Location: Mannheim, Germany<br />
* Deadline: January 6, 2016<br />
* Date posted: November 20, 2015<br />
* Contact: queripidia-jobs(At)uni-mannheim(DoT)de<br />
<br />
The Information Retrieval and Natural Language Processing Group at the University of Mannheim invite applications for<br />
<br />
'''ONE PHD STUDENT IN STATISTICAL NLP / IR / MACHINE LEARNING'''<br />
<br />
The student is expected to contribute to a project on Knowledge Consolidation and Organization for Query-specific Wikipedia Construction under the principal investigator Laura Dietz. The goal of the research project is to make information on the Web accessible in a Wikipedia-like form through a query-driven interaction paradigm. This research requires a combination of methods from information retrieval and automatic text understanding to provide the user with a synthesis of the information through summarization, sub-topic identification, and article organization.<br />
<br />
We are particularly interested in candidates with a background in one or several of the following areas:<br />
* statistical text processing (e.g., automatic summarization, event extraction and ordering)<br />
* machine learning<br />
* knowledge base construction<br />
* information retrieval<br />
* distributed large-scale processing<br />
<br />
Applicants '''must have a Masters degree''' (or obtain it in the near future) in Computer Science, Natural Language Processing or Machine Learning with previous research experience in information retrieval and human language technologies is a plus. The successful candidate is expected work under limited supervision, and publish papers at top level conferences and journals and collaborate with other members of the research group.<br />
<br />
Duration: initially one year (starting in Spring 2016) with possible extension of three years.<br />
<br />
Salary range: according to German public scale TV-L 13 100% (full time, commensurate with experience and qualifications, ranging between 3200 and 4.600 Euro before taxes).<br />
<br />
'''Please submit your application per e-mail (queripidia-jobs(At)uni-mannheim(DoT)de) as a single PDF.''' This PDF should include a short research statement, CV, copy of university degrees, a list of publications and published software and contact details of three references. All applications sent before January 6, 2016 will receive full consideration. The position remains open until filled.<br />
<br />
The Data and Web Science Group is a joint lab of several professors covering diverse topics on managing, integrating and mining large-amounts of heterogeneous information within enterprise and open Web contexts. Further information about the group can be found at http://dws.informatik.uni-mannheim.de/ .<br />
<br />
The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.<br />
<br />
Please contact Laura Dietz (queripidia-jobs(At)uni-mannheim(DoT)de) for informal enquiries.<br />
<br />
Job posting at: http://bit.ly/1MWXjo1<br />
<br />
<br />
== Research position in Natural Language Processing/Text Mining, University of Manchester ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Postdoctoral Research Fellow<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: October 19, 2015<br />
*Date posted: November 15, 2015<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a senior research fellow in Clinical Text Mining at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk) , School of Computer Science, University of Manchester.<br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical/clinical Natural Language Processing/Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, Coling, etc., and in high quality journals; excellent Java skills; proven ability to develop research proposals independently.<br />
<br />
The objectives of this post are to conduct research into extracting complex information from the scientific literature and clinical case reports to facilitate the discovery of biomarkers using adaptive natural language processing and text mining methods.<br />
* Duration of post: 1st November 2015 for 48 months<br />
* Salary: £38,511 to £42,067 per annum<br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
<br />
The project involves collaboration with a large team working in a newly created interdisciplinary research centre (Manchester Molecular Pathology Innovation Centre, MMPathIC) funded by MRC/EPSRC, focusing on personalised medicine, improving diagnosis and treatment of inflammatory diseases, validating and evaluating biomarkers for improving patient outcomes. <br />
<br />
Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=10521<br />
<br />
== PhD Position: Deep Learning and Random Forest for Argumentation Mining ==<br />
*Employer:University of Liège, Liège, Belgium<br />
*Title: PhD Candidate<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Liège, Belgium<br />
*Deadline: November 23, 2015<br />
*Date posted: October 8, 2015<br />
*Contact: ashwin.ittoo@ulg.ac.be<br />
<br />
The overall goal of this PhD project is to contribute to and advance the nascent field of AM. The selected candidate will have the opportunity to develop novel AM algorithms, which will then be applied to online reviews to evaluate their performance and to determine whether the presence of argumentative patterns are predictive of the helpfulness of online reviews. <br />
<br />
The candidate will investigate the performance of two recent machine learning paradigms, Deep Learning and Random Forests. The candidate will develop a sound understanding of these paradigms and propose novel Deep Learning and Radom Forest algorithms for AM. Other recent machine learning paradigms, in particular, minimally-supervised learning and distant supervision, will also be investigated. The proposed algorithms will be applied to online reviews in order to automatically detect argumentative patterns from the textual contents and determine whether the presence of these patterns influence the reviews’ helpfulness scores of <br />
<br />
Several corpora are already available for evaluation: product and service reviews from Amazon (books, movies), YELP and TripAdvisor. In addition, access to the Penn Discourse TreeBank (PDTB) is also available.<br />
<br />
The selected candidate will be based at the HEC Management School, the University Liège, within the Operations department. Members of this department are engaged in research and teaching in “quantitative methods” (Operations Research, Machine Learning/Data Mining/Analytics, Enterprise Information Systems, Supply Chains and Logistics). The candidate will also collaborate with other international scholars in Japan, the Netherlands and France.<br />
<br />
The PhD project will span over a period of '''4 years''' and the candidate will be hired as a full-time PhD scholar. The '''gross salary will be around 2150 EUR per month (net: ~ 1800-1990 EUR)'''.<br />
Interested candidates are required to send their '''CV (incl. publications if any)''' and a '''letter of motivation''' via e-mail to Prof. Ashwin Ittoo, '''ashwin.ittoo@ulg.ac.be by 23rd November 2015'''. Please clearly indicate ‘PhD application’ in the subject line. Only those candidates deemed most suitable for the research position will be contacted. The starting date is negotiable, but we would prefer candidates who could start soonest. <br />
<br />
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<br />
== Research Associate in Natural Language Processing and Machine Learning, National Centre for Text Mining, University of Manchester ==<br />
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK<br />
*Title: Research Associate<br />
*Speciality: Natural Language Processing, Text Mining<br />
*Location: Manchester, UK<br />
*Deadline: October 3, 2015<br />
*Date posted: September 25, 2015<br />
*Contact: sophia.ananiadou@manchester.ac.uk<br />
<br />
Applications are invited for a researcher in NLP and machine learning at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), School of Computer Science, University of Manchester.<br />
<br />
The candidate will be joining a strong team with 10+ staff at NaCTeM carrying out cutting edge research in NLP, biomedical text mining and machine learning. The post is funded by the Medical Research Council and focuses on developing new algorithms for unsupervised and semi-supervised methods in information extraction, topic analysis, active learning, text classification using deep learning/neural networks to support the development of systematic reviews at the National Institute for Health and Care Excellence.<br />
<br />
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing and Machine Learning; excellent knowledge in unsupervised NLP methods, deep learning, neural networks; excellent knowledge in topic analysis, clustering and classification; track record of high-quality papers in conferences such as ACL, EMNLP, etc., and excellent programming skills.<br />
<br />
* Duration of post: 1st November 2015 for 24 months<br />
* Salary: £30,434 to £37,394 per annum <br />
<br />
'''Research Environment '''<br />
<br />
The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems.<br />
NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".<br />
NaCTeM is collaborating closely with the newly created Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST) in Japan (https://unit.aist.go.jp/airc//index.en.html), which focuses among others on data-knowledge integration, machine learning, natural language processing and text mining. The candidate will benefit from research stays and interactions with the team in Japan.<br />
<br />
Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)<br />
<br />
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=103224.<br />
<br />
<br />
<br />
==Research Positions at AIRC (Artificial Intelligence Research Center), Japan==<br />
*Employer: Artificial Intelligence Research Center (AIRC), National Institute for Advanced Industrial Science and Technology (AIST)<br />
*Title: Post-doctoral research fellows<br />
*Speciality: Machine Learning, Deep Learning, Neuro-Computing, Natural Language Processing, Text Mining<br />
*Location: Tokyo, Japan<br />
*Deadline: October 16, 2015<br />
*Date posted: September 25, 2015<br />
*Contact: airc-recruit-ml@aist.go.jp<br />
<br />
Applications are invited for several positions in Artificial Intelligence at the Artificial Intelligence Research Center (AIRC) (https://unit.aist.go.jp/airc//index.en.html) under the auspices of the National Institute for Advanced Industrial Science and Technology (AIST) (http://www.aist.go.jp/index_en.html). <br />
Successful candidates will join a strong and expanding team of 35+ full-time researchers carrying out cutting edge research in AI. <br />
<br />
Research at AIRC includes Machine Learning, Deep Learning, Planning and Search, Text Mining, NLP, Pattern Recognition, Brain Inspired Computation, and infrastructures for AI.With strong research links to industrial partners, there is a particular emphasis on applications of AI technology to real world problems as well as research into theories and fundamental AI technologies. We work in close cooperation with partners in both the private and public sector to cover a broad range of AI applications, including:<br />
<br />
<br />
* Artificial Intelligence for Human Life: Health-care, Smart city and Smart home, Innovative Retailing and Tourism, etc.<br />
* Artificial Intelligence for Manufacturing and Engineering: Intelligent Robots, Intelligent planning and control of manufacturing plants, etc.<br />
* Artificial Intelligence for Big Sciences: AI applications in Bio-Medical Science and Material Science, Geology, Computational Sociology, etc. <br />
<br />
<br />
<br />
The advertised posts are funded by a project supported by NEDO (http://www.nedo.go.jp/english/index.html), which aims to establish a core research center for AI in Japan. Depending on the expertise and interest of the candidate, s/he will focus either on basic research or application related research of AI to real world problems. AIRC will carry out research in close cooperation with national or international research institutions such as Riken, CMU, Toyota Technology Institute in Chicago, the University of Manchester and DFKI. <br />
<br />
<br />
Candidates should have a PhD in Computer Science with an emphasis on one of the following areas: Machine Learning, Deep Learning, Neuro-Computing, Planning and Search, Natural Language Processing, Text Mining, and Algorithms and Infrastructures for Big Data Analysis. Excellent programming skills and an excellent track-record of high-quality papers in top-tier conferences and journals would be a definite advantage.<br />
<br />
<br />
We have three categories of post-doctoral research fellows. The duration of employment for all three categories is initially 24 months, with a possible extension of 36 months or longer, depending on performance. The starting date of employment will be 1st December 2015 at the earliest.<br />
<br />
* Category A: Post-Doctoral Research Fellow - Salary 5,500,000 JPY to 7,000,000 JPY per annum<br />
* Category B: Senior Post-Doctoral Research Fellow - Salary 7,000,000 JPY to 10,000,000 JPY per annum<br />
* Category C: Distinguished Research Fellow - Salary 10,000,000 JPY per annum<br />
<br />
<br />
'''Research Environment'''<br />
<br />
<br />
AIST is one of the largest publicly funded research institutes in Japan and a single research institute under the Ministry of Economy, Trade and Industry (METI). AIRC is the newest research center within AIST, established in May, 2015. As a core research center of AI in Japan, we have been establishing close cooperation with researchers at Japanese and international institutes, which include the University of Tokyo, Tokyo Institute of Technology, Riken, Osaka University, Tohoku University, National Institute of Informatics, Toyota Technology Institute in Chicago, CMU, University of Manchester and DFKI. <br />
<br />
<br />
AIRC is located in Odaiba, which is in one of the central districts of Tokyo, a bustling international city and the capital of Japan. Tokyo offers both the modern urban lifestyle of Japan as well as a rich Japanese heritage. <br />
<br />
Interested candidates are invited to send, via electronic mail, the following items to the Director of Artificial Intelligence Research Center (AIST), Prof. Junichi Tsujii (airc-recruit-ml@aist.go.jp):<br />
<br />
* A cover letter that clearly indicates their main research interests<br />
* Curriculum Vitae <br />
* The contact details of 3 referees <br />
* Copies of maximum of 3 publications that you have (co-)authored, and which are representative of your past research achievements. Each publication should be accompanied by a short summary that highlights its major contributions<br />
* An agenda of future research goals. This should be no longer than one page, including figures<br />
<br />
Informal enquiries can be made to airc-recruit-ml@aist.go.jp<br />
<br />
<br />
NOTE: Please send your application to airc-recruit-ml@aist.go.jp directly via e-mail, and not by post. It is NOT necessary to follow the specific CV formats specified on the AIRC website.<br />
<br />
<br />
<br />
==Open Rank Tenure Line Position in Linguistics at Northwestern University==<br />
*Employer: Northwestern University<br />
*Title: Tenure-Line Professor (open rank)<br />
*Speciality: Open area<br />
*Location: Evanston, IL, USA<br />
*Deadline: December 1, 2015<br />
*Date posted: August 31, 2015<br />
*Contact: matt-goldrick@northwestern.edu<br />
<br />
The Department of Linguistics at Northwestern University seeks to fill a tenure-line position (open rank) with a start date of September 1, 2016. We are looking for candidates who pursue an integrated approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The candidate will join a vibrant interdisciplinary language sciences community including researchers from cognitive science, cognitive neuroscience, computer science, philosophy, psychology, and speech science.<br />
<br />
We seek exceptional candidates with forward-looking research programs that hold the promise of future external funding. Applicants that wish to be considered for appointment at the rank of Associate Professor or Professor are expected to have a record of excellence in research and teaching, success in obtaining external funding, and to have held both internal and external leadership roles. <br />
<br />
To receive fullest consideration, applications should arrive by December 1, 2015. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names of three references (with their contact information). Please visit http://www.linguistics.northwestern.edu/ for online application instructions.<br />
<br />
E-mail inquiries should be directed to Matt Goldrick, Chair (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.<br />
<br />
<br />
== One PHD / POSTDOC position in Text Analysis at the University of Mannheim ==<br />
* Employer: The Data and Web Science Research Group, University of Mannheim, Germany<br />
* Title: PhD or Postdoctoral Research Fellow <br />
* Topics: Natural Language Processing<br />
* Location: Mannheim, Germany<br />
* Deadline: September 15, 2015<br />
* Date Posted: August 20, 2015<br />
* Contact: sfb884@informatik.uni-mannheim.de<br />
<br />
The researcher is expected to contribute to the C4 project on “Measuring a common space and the dynamics of reform positions” within the DFG-funded Collaborative Research Centre (SFB) 884 “Political Economy of Reforms” (http://reforms.uni-mannheim.de) at the University of Mannheim. The topic of the PhD will focus on exploiting computational methods for analysing discourse phenomena like, e.g., uncertainty, vagueness and bias in political texts. This is a joint collaboration between the Natural Language Processing and Information Retrieval group (Prof. Simone Paolo Ponzetto) and the Chair of Artificial Intelligence (Prof. Heiner Stuckenschmidt), which will also involve close collaboration with project partners at the Department of Political Science (Prof. Dr. Nicole Rae Baerg, Prof. Dr. Thomas Gschwend), ranked as the best Political Science Department in Germany in different national and international university rankings. The student will be located at the Data and Web Science Group (DWS) of the University of Mannheim, one of leading centers for Data Science in Germany.<br />
<br />
We are particularly interested in candidates with a background in one or several of the following areas:<br />
<br />
* statistical semantics and discourse processing<br />
* machine learning and natural language processing<br />
* discourse analysis<br />
* automated text-based scaling<br />
<br />
Applicants should have a Masters degree (or obtain it in the near future) in Computer Science, Natural Language Processing, Machine Learning or Social Science and have previous experience in applying human language technology. <br />
<br />
'''Duration:''' initially one year (starting in Fall 2015) with possible extension to 3-5 years.<br />
'''Salary range:''' according to German public scale TV-L 13 100% (full time, ranging between 3200,- and 4.600,- Euro before taxes depending on qualification). <br />
<br />
Applications can be made per e-mail (sfb884@informatik.uni-mannheim.de) and should include a short research statement, CV, copy of university degrees and transcripts and - if available - a copy of the master thesis, as well as list of publications and published software. Further information about the groups can be found at http://dws.informatik.uni-mannheim.de/. All documents should be e-mailed as a single PDF. All applications sent before '''September, 15 2015''' will receive full consideration. The positions remain open until filled.<br />
<br />
The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.<br />
<br />
Please contact Simone Paolo Ponzetto (simone(At)informatik(DoT)uni-mannheim(DoT)de) and Heiner Stuckenschmidt (heiner(At)informatik(DoT)uni-mannheim(DoT)de) for informal enquiries.<br />
<br />
<br />
<br />
<br />
<br />
== Postdoctoral Fellow in NLP for EEG Analysis at Temple University ==<br />
* Employer: The Neural Engineering Data Consortium, College of Engineering, Temple University<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing, Machine Learning, Big Data, EEG Analysis<br />
* Location: Philadelphia, PA<br />
* Deadline: Open until filled<br />
* Date Posted: August 12, 2015<br />
* Contact: Joseph Picone (joseph.picone@gmail.com)<br />
<br />
'''Research focus''': The Neural Engineering Data Consortium (NEDC) at Temple University invites applications for a Postdoctoral Fellow position in the area of automated EEG analysis. The Postdoctoral Fellow will contribute to a project that enables comparative research by automatically uncovering clinical knowledge from a vast BigData archive of clinical EEG signals and EEG reports collected over the past 14 years at Temple University Hospital (see www.isip.piconepress.com/projects/tuh_eeg for more information). We are developing a proof-of-concept based on the discovery of patient cohorts and provide an annotated BigData archive as well as the software that enabled the annotations and the generation of the patient cohort retrieval system. The candidate will be involved in overseeing the generation of labeled data for machine learning training, developing algorithms to automatically uncover and model structure based on deep<br />
learning principles, implementing an active learning approach that minimizes the amount of labeled data needed and supervising research to automatically extract medical concepts from EEG reports. A large portion of the project focuses in extraction of information from unstructured text, and hence, expertise in natural language processing is important.<br />
<br />
'''Supervisor''': Iyad Obeid, PhD and Joseph Picone, PhD<br />
<br />
'''Required skills''': The candidate’s primary expertise will be in natural language processing and/or computational linguistics. Proficiency in machine learning and big data techniques is highly desirable. Software engineering experience is also desired.<br />
<br />
'''Education''': A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required. <br />
<br />
'''Length of appointment''': This position is for three years.<br />
<br />
'''Available''': October 1, 2015.<br />
<br />
'''Compensation''': $42,000/year (NIH standard scale applies).<br />
<br />
'''To apply''': Send a CV and cover letter to joseph.picone@gmail.com (see http://www.isip.piconepress.com/images/memorabilia/temple/20150811_postdoc/postdoc_announcement_v00.pdf for more details) <br />
<br />
<br />
== Postdoctoral Fellow in Sentiment Analysis at McMaster University ==<br />
* Employer: Department of Linguistics, Department of Computing and Software, McMaster University<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Sentiment Analysis, Natural Language Processing<br />
* Location: Hamilton, ON, Canada<br />
* Deadline: Open until filled<br />
* Date Posted: July 24, 2015<br />
* Contact: Victor Kuperman (vickup@mcmaster.ca)<br />
<br />
'''Research focus''': Successful applicants will be working closely with a vibrant cross-faculty team of linguists, psychologists and computer scientists. The selected candidate will contribute to a research program that explores individual and group (gender, age) variability in perception and regulation of emotion. Primary responsibilities will include investigating new algorithmic techniques for identifying fine-grained sentiment on textual data, and semi-structured data, including social media. Equally important to the project is the development of lexical-semantic tools allowing big data analyses of text corpora for the purposes of text classification, topic modeling, development of semantic networks, and estimation of semantic similarity.<br />
<br />
'''Supervisor''': Victor Kuperman, PhD, Fei Chiang, PhD<br />
<br />
'''Required skills''': The candidate’s primary expertise will be in natural language processing, sentiment analysis, and/or computational linguistics. Proficiency in machine learning techniques is highly desirable.<br />
<br />
'''Education''': A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required. <br />
<br />
'''Length of appointment''': This position is for two years.<br />
<br />
'''Available''': August 1st, 2015.<br />
<br />
'''Compensation''': $50,000/year.<br />
<br />
'''To apply''': see application procedure at http://www.cas.mcmaster.ca/~fchiang/misc/postdoc.pdf <br />
<br />
<br />
<br />
== Postdoctoral Fellow in Natural Language Processing at Brigham and Women's Hospital / Harvard Medical School ==<br />
* Employer: Brigham and Women's Hospital / Harvard Medical School<br />
* Title: Postdoctoral Research Fellow<br />
* Topics: Natural Language Processing<br />
* Location: Boston, MA<br />
* Deadline: Open until filled<br />
* Date Posted: July 11, 2015<br />
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)<br />
<br />
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of open-source natural language processing framework software and high-dimensional predictive models that utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.<br />
<br />
'''Supervisor''': Alexander Turchin, MD, MS, FACMI<br />
<br />
'''Required skills''': strong programming and system development skills; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills. Experience in programming in Perl and .NET and experience with natural language processing and medical terminologies / ontologies is a strong plus.<br />
<br />
'''Education''': PhD in computer science, biomedical informatics, linguistics, or related discipline, MD or an equivalent degree.<br />
<br />
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.<br />
<br />
'''Available''': August 1st, 2015.<br />
<br />
'''Compensation''': according to NIH (NRSA) stipend levels.<br />
<br />
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu. <br />
<br />
<br />
== Data Scientist - Unstructured Data at Civis Analytics ==<br />
* Employer: [https://civisanalytics.com Civis Analytics]<br />
* Title: Data Scientist - Unstructured Data<br />
* Topics: Natural Language Processing, Machine Learning, Deep Learning, Big Data Analytics, Computer Vision, Speech Processing, Algorithm Development<br />
* Location: Chicago, IL<br />
* Deadline: Open until filled<br />
* Date Posted: June 23, 2015<br />
* Apply Online: [https://civisanalytics.com/careers civisanalytics.com/careers]<br />
* Questions: apply@civisanalytics.com<br />
<br />
<br />
'''Who We Are'''<br />
<br />
Civis Analytics is building a data-driven world. We create technologies that empower organizations to unlock the truth hiding in their own data—transforming them into smart organizations that are ready to thrive.<br />
<br />
While our history is rooted in political campaign targeting, we’re now partnering with intelligent organizations in healthcare, media, education, and a range of other domains. We’re also building cloud-based products to do data science better.<br />
<br />
We're solving the world's biggest problems with big data. Through research, experimentation, and iteration, we’re transforming how organizations do analytics. Our clients range in scale and focus from local to international, all empowered by our individual-level, data-driven approach.<br />
<br />
Our incredible team of engineers, statisticians, researchers, and solution seekers come from all over the world with diverse backgrounds in Fortune 500 companies, international non-profits, Ivy League academia, and even actual rocket science.<br />
<br />
'''Why should you join our team?'''<br />
<br />
We are already hard at work on solving the world’s toughest problems with Big Data – working with organizations to analyze and understand their individual level data to improve outcomes and implement organizational change. We use cutting edge data science techniques, and we want to continue be on the forefront of innovation in our field.<br />
<br />
We are ''smart'', ''fun'', and ''a little bit weird''. ''Does this sound like you?'' <br />
<br />
'''Position Overview'''<br />
<br />
The Research and Development team is responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company. Our diverse work includes predictive analytics, algorithm development, experimental design, visualization, and survey research.<br />
<br />
As a Data Scientist on our Chicago-based Research and Development team, you will work closely and collaboratively with analysts and engineers to develop and operationalize the techniques that quantify and solve big, meaningful problems. Our team dives deeply into big problems and works in a variety of areas. With a specialization in unstructured data, this Data Scientist role will apply techniques from fields such as machine learning, applied statistics, natural language processing, computer vision, and speech processing to the growing unstructured datasets being collected at Civis. Because the majority of the world’s information is unstructured, being able to leverage these diverse and voluminous data sources adds tremendous value to Civis products and research. In this role, you will be a critical voice shaping both how unstructured data informs existing Civis products and services, and how it leads to the development of entirely new ways of serving our clients, novel to the industry as a whole.<br />
<br />
We are looking for individuals from a diversity of backgrounds with demonstrated quantitative and problem-solving skills. We value creativity, hard work, and on-the-job-excellence and offer competitive compensation and benefits packages. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States.<br />
<br />
'''Requirements'''<br />
<br />
'''MINIMUM QUALIFICATIONS'''<br />
<br />
* Bachelor’s degree in a quantitative field, such as computer science, statistics, machine learning, or electrical engineering<br />
* Knowledge of and practical experience in applying the methodology of one or more unstructured data analysis fields, such as natural language processing, speech processing, or computer vision<br />
* Familiarity with statistical packages such as R, Stata, or in the Python scientific stack (NumPy, SciPy, scikit-learn, pandas)<br />
* Experience with common toolkits for unstructured data analysis, such as Theano, Torch, open-cv, the Stanford NLP tools, HTK, and Kaldi<br />
* Experience with SQL databases<br />
* Strong programming skills<br />
* Experience identifying and correcting for problems in imperfect data<br />
* An ability and eagerness to constantly learn and teach others <br />
<br />
'''PREFERRED QUALIFICATIONS'''<br />
<br />
* Master’s degree in a quantitative field such as computer science, statistics, machine learning, or electrical engineering<br />
* Significant work experience in applying the methodology of one or more unstructured data analysis fields<br />
* High proficiency in programming with Python, Go, Java, Lua, C, or other languages used for high-performance statistical computing<br />
* Familiarity with architectures for scaling statistical computing to big data applications, such as Hadoop and Spark<br />
<br />
'''How to Apply'''<br />
<br />
Apply online at: [https://civisanalytics.com/careers civisanalytics.com/careers]<br />
<br />
== Postdoctoral Fellow in NLP at University of Pennsylvania ==<br />
* Employer: Dept. of Computer and Information Science, University of Pennsylvania<br />
* Title: Postdoctoral Researcher<br />
* Topics: Natural Language Processing, Unsupervised Learning<br />
* Location: Philadelphia, PA<br />
* Deadline: Open until filled<br />
* Date Posted: June 19, 2015<br />
* Contact: Mitch Marcus (mitch@cis.upenn.edu)<br />
<br />
'''Job Description'''<br />
<br />
Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania. This is a full time position for 24 months, starting immediately.<br />
<br />
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora. The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years, and we intend to shamelessly exploit them all. <br />
<br />
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics.<br />
<br />
'''Requirements'''<br />
<br />
The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record. Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. <br />
<br />
'''How to Apply'''<br />
<br />
Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided above. <br />
<br />
<br />
== Postdoctoral Fellow in Machine Learning/Computational Linguistics for Child Language Acquisition ==<br />
* Employer: University of Liverpool<br />
* Title: Post-doctoral fellow <br />
* Topics: machine learning, computational linguistics, corpus linguistics, algorithm development, deep learning, speech processing<br />
* Deadline: 28th August 2015<br />
* Date Posted: 2nd June 2015<br />
* Apply: http://www.liv.ac.uk/working/jobvacancies/currentvacancies/research/r-588063/<br />
<br />
'''Job Description'''<br />
<br />
We are recruiting for post-doctoral fellow to work on the application of machine learning/computational linguistic techniques to child language acquisition.<br />
<br />
You should have a PhD in Computer Science/Engineering/Linguistics/Psychology and have experience with machine learning algorithms applied to language data and have published your work in conference proceedings or journals. Experience with auditory speech processing, deep learning, cloud computing, and GPU programming is desirable. The post is available for 2 years.<br />
<br />
The computational community has developed a wealth of algorithms that can automatically discover linguistic units and dependencies between these units and these algorithms have been applied to language parsing and generation. In contrast, child language researchers often study child language using human coding of detailed linguistic information. The goal of this project is to develop a bridge between these two approaches. Machine learning techniques would give child language researchers ways to pull out relevant utterances that could be subject to greater processing. Child language analyses could be compiled into test sets that could be used to evaluate machine learning algorithms. In this post, you will develop machine learning algorithms for child language and also develop a web site that will enhance the ability of machine learning researchers and child language researcher to share data and algorithms. The research topics and approaches are open to negotiation. Children have some of the most advance language learning algorithms and understanding how they learn language could lead to new insights for computational approaches to language.<br />
<br />
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the new ESRC International Centre for Language and Communicative Development, a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster.<br />
<br />
More information is available here:<br />
https://sites.google.com/site/sentenceproductionmodel/news<br />
<br />
==Postdoctoral Fellow and Software Engineer postions in biomedical natural language processing, machine learning and biomedical informatics==<br />
* Employer: UMass Medical School Worcester<br />
* Title: Post-doctoral fellow or Software Engineer<br />
* Topics: Biomedical natural language processing, machine learning, bioinformatics, algorithm development, big data analytics<br />
* Deadline: until filled<br />
* Date Posted: 24 May 2015<br />
* apply by contacting elaine.freund@umassmed.edu<br />
<br />
'''Job Description'''<br />
<br />
We are recruiting for multiple positions at levels from Post Doctoral Fellow to Software Engineer to participate research and software development in biomedical natural language processing (NLP) and biomedical informatics. The group’s research (http://www.bio-nlp.org/index.php/projects) involves developing algorithms and tools for gathering, analyzing and interpreting heterogeneous data from multiple sources both clinically and research related. Recruits will lead development efforts in web service tools and search engines that: retrieve and summarize big data in biomedical domain, automatically extracting information from pdf files and extracting text from images, integrate novel biomedical text mining algorithms into the web tools and search engines to enable intelligent semantic search, and mining electronic health record data for pharmacovigilance. <br />
<br />
If you are highly motivated and passionate about research in big data processing or software engineering or have in-depth knowledge and hands on implementation experience with web service tools and are interested in learning more about us, please contact elaine.freund@umassmed.edu with your resume or CV and a cover letter. <br />
<br />
General Summary of Postdoc Fellow Position: PhD in Computer Science, computational linguistics or Biomedical Informatics with expertise in natural language processing, machine learning or information retrieval with excellent writing and communication skills and ability to work with the research team. <br />
<br />
General Summary of Software Engineer Position:<br />
Under the direction of the Faculty or designee, the Software Engineer I assists with the design, development, implementation and integration of web service tools, search engines, utilities, applications and enhancements in a complex medical/academic research computing environment. <br />
<br />
==Research Scientist in natural language processing, machine learning, knowledge discovery, data analytics at IBM Research-Almaden==<br />
* Employer: IBM Research<br />
* Title: Research Scientist<br />
* Topics: Nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics<br />
* Location: San Jose, California, USA<br />
* Deadline: 1 June 2015<br />
* Date Posted: 6 May 2015<br />
* Online application: https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0751127<br />
<br />
'''Job Description'''<br />
<br />
IBM Research - Almaden is looking for researchers to join the Natural Language Processing (NLP), Entity Resolution and Discovery (NERD) Department. Our research focuses include high-value content creation from variety of public and third-party data sources, scalable and usable analytics tools for individual stages in analyzing such data sources, such as text analytics, entity resolution, large-scale machine learning, techniques and methods for scalable and flexible indexing and querying support over enriched content, and consumable interfaces for accessing such data sources, including natural language interfaces. An example project is SystemT (http://ibm.co/1Cdm1Mj).<br />
<br />
We are currently looking for a Research Staff Member to conduct research with large scale real-world heterogeneous data in the area of advanced analytics, such as nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics. This role generates highly novel ideas, both theoretical and experimental, in a specific engineering or scientific discipline and invents and designs complex products and processes. This position may be involved in engineering these ideas to an advanced state of feasibility by evaluating ideas and plans and participating in their design and development. The full cycle of innovation to delivery is typically a multiple-year effort.<br />
<br />
The candidate is also responsible for internally and externally disseminating the results of such activities through publications, patent disclosures, seminar participation, technical documentation, etc. The candidate represents IBM at professional conferences, in professional societies and universities and functions as an internal consultant in the areas of professional expertise.<br />
<br />
'''Required'''<br />
<br />
* Master's Degree<br />
* At least 1 year experience in developing advances in Computer Science disciplines<br />
* At least 1 year experience in performing Scientific Research<br />
* English: Intermediate<br />
<br />
'''Preferred'''<br />
<br />
* Doctorate Degree in Information Technology<br />
* At least 3 years experience in developing advances in Computer Science disciplines<br />
* At least 3 years experience in performing Scientific Research<br />
* English : Fluent<br />
<br />
'''Additional Information'''<br />
<br />
The World is Our Laboratory: No matter where discovery takes place, IBM researchers push the boundaries of science, technology and business to make the world work better. IBM Research is a global community of forward-thinkers working towards a common goal: progress.<br />
<br />
IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.<br />
<br />
<br />
==PhD position in statistical language modelling==<br />
* Employer: Cardiff University<br />
* Title: PhD scholarship<br />
* Topics: Statistical language modelling, relation extraction, social media<br />
* Location: Cardiff, UK<br />
* Deadline: 1 June 2015<br />
* Date Posted: 7 April 2015<br />
* Online application: http://courses.cardiff.ac.uk/funding/R2497.html<br />
<br />
'''Job Description'''<br />
<br />
Applications are invited for a PhD Scholarship at the Cardiff School of Computer Science & Informatics in the area of statistical language modelling. Specifically, the aim of the project will be to develop methods for modelling the meaning of natural language terms, based on data from social media and other web sources. For example, by analysing the tags associated with Flickr photos, the developed methods will be able to learn that a church is a kind of building, that churches tend to be larger than typical buildings and that chapels are similar to churches. The results of this project will be used to improve methods from artificial intelligence for commonsense reasoning, and will among others enable more intelligent web search engines.<br />
<br />
'''Funding and eligibility'''<br />
<br />
This studentship consists of full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£14,057 p.a. for 2015/16, updated each year). This studentship is open to students of any nationality. Students classified as international for fee purposes have to self-fund the difference between home and international fees.<br />
<br />
Candidates should:<br />
<br />
* either have (or expect to have by Autumn 2015) a good honours degree in a relevant discipline (minimum 2:1);<br />
* or have a masters degree with distinction in the research dissertation in a relevant discipline;<br />
* or have professional qualifications deemed by Cardiff University to be equivalent to the above;<br />
* or be over 25 and have relevant work experience in a position of responsibility.<br />
<br />
The methods will rely heavily on methods from statistics and linear algebra, hence a strong background in mathematics will be required, in addition to excellent programming skills. A strong mathematical background and excellent programming skills will also be required.<br />
<br />
Applicants are particularly welcomed from candidates with a background in computer science.<br />
<br />
If your first language is not English you must provide evidence of competence in English. Our standard requirement is an overall IELTS result of at least 6.5, with a minimum of 6.5 in writing, and a minimum of 6.0 in speaking, listening and reading.<br />
<br />
'''Further information'''<br />
<br />
For further information and instructions on how to apply, please see http://courses.cardiff.ac.uk/funding/R2497.html<br />
<br />
==Postdoctoral Researcher in NLP at U.S. Army Research Lab==<br />
* Employer: U.S. Army Research Lab, Adelphi Laboratory Center<br />
* Title: Postdoctoral Researcher<br />
* Topics: Natural Language Processing<br />
* Location: Adelphi, MD, USA<br />
* Deadline: Open until filled<br />
* Date Posted: March 17, 2015<br />
* Contact: Dr. Stephen Tratz (stephen.c.tratz.civ@mail.mil)<br />
<br />
'''Job Description'''<br />
<br />
The Multilingual Computing Branch (MLCB) at the U.S. Army Research Laboratory's Adelphi Laboratory Center, located in the Washington, D.C. metro area, is seeking to hire new post-doctoral fellows. MLCB has several ongoing efforts in computational linguistics/natural language processing, including active projects in machine translation, human-robot communication, and social media analysis. The branch is also pursuing new interdisciplinary initiatives to address the language processing challenges in cyber-security and video analytics.<br />
<br />
Candidates should have substantial research experience in machine learning methods (e.g., deep neural networks) as applied to emerging areas involving computational linguistics. Areas of interest include: text/video analytics, computational social science, machine translation, domain adaptation, data selection, low-resource language processing, morphologically complex languages, knowledge representation and reasoning, spoken language interfaces and dialogue, and multimedia processing.<br />
<br />
The lab encourages external collaboration and maintains multiple partnerships with universities and research institutions, which enable faculty and student exchanges as well as joint research and publishing (http://www.arl.army.mil/www/default.cfm?page=93). ARL’s new open campus initiative is attracting national and international partners from academia and industry to work with ARL scientists and engineers in areas of common research interest (see http://www.arl.army.mil/www/default.cfm?page=2357), and ARL researchers have begun releasing open source code via GitHub (see http://www.army.mil/article/141734/Army_cyber_defenders_open_source_code_in_new_GitHub_project/). ARL facilities include multiple high-end supercomputing clusters with over 10,000 cores and capable of at least 350 TFlops. <br />
<br />
'''Requirements'''<br />
<br />
* Ph.D. or equivalent research experience in computer science, statistics, mathematics, or related field<br />
<br />
'''How to Apply'''<br />
<br />
If interested, please email your CV and the names and contact information of three or more references to Dr. Stephen Tratz at the email provided above.<br />
<br />
==Postdoctoral Researcher in NLG for Narrative==<br />
* Employer: Liquid Narrative Group, North Carolina State University <br />
* Title: Postdoctoral Research Scholar<br />
* Topics: Natural Language Generation, Narrative Generation, Knowledge Representation, AI Planning<br />
* Location: Raleigh NC, USA<br />
* Deadline: Open Until Filled<br />
* Date Posted: March 10, 2015<br />
* Online Application: http://jobs.ncsu.edu/postings/40524<br />
<br />
'''Job Description'''<br />
<br />
The Liquid Narrative group at North Carolina State University is seeking a postdoctoral researcher to collaborate on a large-scale narrative generation project. The goal of this project is to build computational tools for the use of narrative in sense-making tasks. Research thrusts include the creation of formalisms for representing story and discourse knowledge and the development of narrative generation algorithms able to create multiple narrative discourses from a given story, adapt these discourses to an audience, and elicit different effects such as surprise or suspense. This project aims at creating a large-scale narrative-generation system that can extract story data from various sources (e.g., video game logs) and create narratives in and across several media such as text, animated movies or maps.<br />
<br />
The postdoctoral researcher will contribute to the design and development of narrative generation and summarization technologies, focusing on the microplanning aspect of text generation. In particular, he or she will extend an existing narrative discourse generation prototype that outputs basic sentences using the SimpleNLG library. Our aim is to update this architecture by integrating an NLG system such as FUF/Surge, KPML or RealPro. To improve the quality of the generated text, the postdoctoral researcher will work on topics such as: aggregation, generation of referring expressions, discourse markers insertion, lexical choice and/or other aspects of realization that are specific to narrative as a genre.<br />
<br />
He/she may also participate in research efforts on the automated generation of multimedia presentations involving text, video and maps. He/she is expected to collaborate in performing scientific evaluations of the systems, and in writing academic research papers.<br />
<br />
'''Requirements'''<br />
<br />
The applicant must hold a PhD degree, preferably in the area of computational linguistics or natural language generation. He/she should have:<br />
* Experience with developing NLG systems<br />
* Excellent software-design and problem-solving skills<br />
* Good programming skills<br />
* Excellent written and oral communication skills<br />
<br />
Experience in the following areas would be a plus:<br />
* Automated discourse planning technologies<br />
* Dialogue generation<br />
<br />
'''Position details'''<br />
<br />
This is a full-time position.<br />
Expected start date is April 1, 2015 and the initial funding for the position runs through December 31, 2015. The position may be extendable depending on availability of funds.<br />
<br />
Interested candidates should view the official Human Resources posting and submit applications through the NC State University HR web page at http://jobs.ncsu.edu/postings/40524 <br />
<br />
NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran. Individuals with disabilities requiring disability-related accommodations in the application and interview process, please call 919-515-3148.<br />
<br />
<br />
==PhD-level Researchers in Language Technology or Computational Linguistics==<br />
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)<br />
* Title: PhD-level Researchers in Language Technology or Computational Linguistics<br />
* Topics: Natural Language Processing, Summarization, Opinion Mining<br />
* Location: Darmstadt (Germany)<br />
* Deadline: open until the position is filled<br />
* Date Posted: March 4, 2015<br />
* Contact: Prof. Iryna Gurevych apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de<br />
<br />
'''Job Description'''<br />
<br />
The newly established Research Training Group „[http://www.aiphes.tu-darmstadt.de Adaptive Information Processing of Heterogeneous Content]“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht-Karls-University Heidelberg is filling several positions for three years, starting as soon as possible:<br />
<br />
PhD-level Researchers in Language Technology or Computational Linguistics<br />
<br />
The positions provide the opportunity to obtain a doctoral degree with an emphasis within one of the following guiding themes:<br />
<br />
* A3: Opinion and Sentiment - extrapropositional aspects of discourse (Univ. of Heidelberg)<br />
* B1: Structured summaries of complex contents (TU Darmstadt)<br />
* B2: Content selection based on linked lexical resources (TU Darmstadt)<br />
* D1: Multi-level models of information quality in online scenarios (TU Darmstadt)<br />
* D2: Manual and Automatic Quality Assessment of Summaries from Heterogeneous Sources (TU Darmstadt)<br />
The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale. <br />
<br />
The goal of AIPHES is to conduct innovative research on multi-document summarization in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment will be developed. AIPHES will investigate a novel summarization scenario for information preparation from heterogeneous sources. There will be close interaction with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite. <br />
<br />
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann), Multimedia Communications (Dr. Rensing). Participants at the Ruprecht-Karls-University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media. <br />
<br />
AIPHES will emphasize close contact between students and their advisors, have regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and will actively support its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.<br />
<br />
'''Requirements'''<br />
<br />
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged. <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht-Karls-University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. The ICL and the NLP department of the HITS jointly run the graduate program „Semantic Processing“ with an integrated research training group “Coherence in language processing: Semantics beyond the sentence”, which has a close connection to the topics in computational linguistics of AIPHES. <br />
<br />
Applications should include <br />
<br />
* a motivational letter that refers to one of the above listed guiding themes,<br />
* a CV with information about the applicant’s scientific work,<br />
* certifications of study and work experience,<br />
* as well as a thesis or other publications in electronic form.<br />
They should be submitted until March 23th, 2015 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de. The interviews may start any time. The positions are open until filled.<br />
<br />
<br />
==Research staff position in Natural Language Processing==<br />
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)<br />
* Title: Research staff position in Natural Language Processing<br />
* Topics: Natural Language Processing, Question Answering<br />
* Location: Darmstadt (Germany)<br />
* Deadline: open until the position is filled<br />
* Date Posted: March 4, 2015<br />
* Contact: Nicolai Erbs erbs@ukp.informatik.tu-darmstadt.de<br />
<br />
'''Job Description'''<br />
<br />
The [https://www.ukp.tu-darmstadt.de Ubiquitous Knowledge Processing Lab] (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a research staff position (TV-TU E13 German payscale) with a focus on question answering and summarization of social media content. This DFG-funded basic [https://www.ukp.tu-darmstadt.de/research/current-projects/qa-eduinf research project] conducts research integrating semantic text analysis, such as semantic role labeling (SRL), into higher-level applications in information access to improve their overall results (Principal Investigator: Prof. Dr. Iryna Gurevych). Thereby, we pay special attention to graph-based techniques. <br />
<br />
The selected candidate will work with a large corpus from a social question-answer platform on the Web. He/she will be expected to identify interesting research problems, research ways of utilizing semantic role labeling in novel NLP tasks, and develop means and resources to evaluate the results. The newly established Research Training Group “[http://www.aiphes.tu-darmstadt.de Adaptive Information Processing of Heterogeneous Content]” (AIPHES) funded by the DFG [3] provides an excellent research environment for this kind of work. The funding is available for the duration of at least two years with an option for extension.<br />
<br />
'''Requirements'''<br />
<br />
We ask for applications from applicants in Computer Science or Computational Linguistics, preferably with completed PhD and research publications. Experience in Question Answering or a related field like summarization or information retrieval is a definite advantage. Excellent graduates of these disciplines willing to work towards a PhD are also encouraged to apply. Ideally, the candidates should have strong research skills as well as demonstrable experience in designing and implementing complex natural language processing (NLP) applications in Java and/or with graph-based algorithms. A very good command of German is a definite plus, since the target corpus is in the German language. Excellent communication skills in English and the ability to work in a team are required.<br />
<br />
Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees. Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: erbs@ukp.informatik.tu-darmstadt.de by 23.03.2015. The position is open until filled.<br />
<br />
<br />
==PhD-position in NLP/Text Mining==<br />
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)<br />
* Title: PhD-position in NLP/Text Mining<br />
* Natural Language Processing, Text Mining<br />
* Location: Darmstadt (Germany)<br />
* Deadline: open until the position is filled<br />
* Date Posted: March 4, 2015<br />
* Contact: Richard Eckart de Castilho (eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de)<br />
<br />
'''Job Description'''<br />
<br />
The Ubiquitous Knowledge Processing Lab (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a PhD student (TV-TU E13 German payscale) in a research project in Natural Language Processing (NLP) for a computer scientist or computational linguist. The project focusses on building an open text-mining infrastructure at the European level (Principal Investigator: Prof. Dr. Iryna Gurevych).<br />
<br />
Thereby, major NLP and Text Mining platforms, including UIMA and GATE, should be made interoperable and applied to knowledge discovery in scientific literature, e.g. entity disambiguation and linking to a background knowledge repository. In the past, the UKP Lab has developed several frameworks such as the Darmstadt Knowledge Processing Repository (DKPro) and UBY. They form the foundation for the research and implementation work to be done. The graduate program Knowledge Discovery in Scientific Literature provides further research environment for the work to be carried out.<br />
<br />
'''Requirements'''<br />
<br />
Applicants in Computer Science or Computational Linguistics must have demonstrable experience in designing and implementing complex natural language processing (NLP) systems or NLP-based applications and the programming language Java as well as strong research skills. Excellent communication skills in English and the ability to work in a team are required. Experience in open-source software development is a plus.<br />
<br />
The following academic qualification is necessary: completion of an M.A./M.Sc. in Computer Science, Computational Linguistics, or a related field.<br />
<br />
Pending the successful completion of the ongoing administrative steps for the project, funding of this position is available from June 1st, 2015 for the duration of three years.<br />
<br />
Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees.<br />
<br />
Interviews may start at any time and will continue until the position has been filled. Email address for inquiries and applications: eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de <br />
<br />
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. The UKP Lab is also home to the unique research initiative "Knowledge Discovery in the Web” which emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. <br />
<br />
The Technische Universität Darmstadt promotes gender equality and in particular encourages women to apply. Preference will be given to physically handicapped persons if they are equally qualified.<br />
<br />
<br />
==Internship position available in Natural Language Processing at Adobe Research==<br />
* Employer: Adobe Systems Incorporated<br />
* Title: NLP Scientist Intern<br />
* Natural Language Processing, Machine Learning, Dialog Systems.<br />
* Location: San Jose, CA<br />
* Deadline: open until the position is filled<br />
* Date Posted: February 24, 2015<br />
* Trung Bui: bui@adobe.com<br />
<br />
'''Description''': <br />
We are looking for an NLP scientist intern who will work on exploring deep learning for mapping between natural language queries and logic form and/or SQL. <br />
<br />
'''Key Qualifications'''<br />
*Experience with semantic parsing, dialog systems.<br />
*Experience with machine learning, deep learning.<br />
*Good programming skills in Java and/or Python<br />
<br />
'''Education'''<br />
M.S. or PhD student in Computer Science or related field<br />
<br />
'''Additional Requirements'''<br />
No.<br />
== Postdoc in Advanced Machine Learning (with an Emphasis on NLP) ==<br />
<br />
*Employer: University of Notre Dame<br />
*Job Number: 4015639<br />
*Date Posted: 02/17/2015<br />
*Application Deadline: Open Until Filled <br />
*Online application: http://www.postdocjobs.com/jobs/jobdetail.php?jobid=4015639<br />
<br />
'''Job Description'''<br />
<br />
The Computer Science Department at the University of Notre Dame in collaboration with the Institute for Intelligent Systems at the University of Memphis anticipates hiring a postdoctoral fellow starting as early as April 1st 2015 for one year and renewable for a second year. The position includes a full time salary and benefits and is jointly funded by sponsored research split between the University of Notre Dame and the University of Memphis. Review of applications will start immediately and continue until the position is filled.<br />
<br />
The successful candidate will conduct research in machine learning applied to dialog-centered natural language understanding. He/she will participate in the development and application of machine learning techniques in the hierarchical and temporal domains to multi-party speech data collected in authentic educational contexts.<br />
<br />
The candidate will work under the supervision of Dr. Sidney D’Mello, who has joint appointments in the Departments of Computer Science and Psychology at Notre Dame, and Dr. Andrew Olney in the Institute for Intelligent Systems at the University of Memphis.<br />
<br />
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within a multi-department multi-institution grant-funded project. The postdoc will be encouraged to build advanced technical skills, strengthen their research portfolios via peer-reviewed publications, develop leadership skills by mentoring students, and gain expertise in authoring collaborative grant proposals.<br />
<br />
'''Required'''<br />
<br />
(1) Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire; (2) Research experience in advanced machine learning techniques for sequential and hierarchical domains (e.g., probabilistic graphical models, sequence tagging, deep learning) ; (3) Evidence of a strong publication record in the aforementioned areas<br />
<br />
'''Desired'''<br />
<br />
(1) Research experience in one or more of the following research areas (acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling) ; (2) Experience working on interdisciplinary projects and/or on educational research; (3) Experience mentoring graduate and undergraduate students <br />
<br />
For more information see the application link above.<br />
<br />
== Software Engineer/NLG Specialist in Sydney, Aus - Natural Lanaguage Generation==<br />
*Employer: Macquarie Group<br />
*Title: Software Engineer/NLG Specialist<br />
*Specialties: Natural Language Generation, Application Development, Linguistics<br />
*Location: Sydney, Australia<br />
*Date posted: 29 January 2015<br />
*Contact information: andy.logan@macquarie.com<br />
*Online application: http://www.careers.macquarie.com/cw/en/job/923649/software-engineers-nlpnlg-programming-equities-research<br />
<br />
'''Job Description'''<br />
*Unique opportunity within the Equities Research space for a Engineer with strong NLG experience<br />
*New Systems Implementation with Opportunity to push the envelope within Research<br />
*Permanent Opportunity – Sydney CBD Location<br />
<br />
'''About the role'''<br />
<br />
We are seeking a Software Engineer to join our Equities Research business team. This is a truly unique opportunity for someone to join Macquarie working on a pioneering project within the business which could be a big game changer. The role will utilise your strong NLG/NLP experience and you will be responsible for building and developing the NLG functionality within the team. If you are interested in gaining commercial experience with NLG, have excellent written communications and have a flair for English grammar, have a passion for finance and in particular Equities Trading and want the opportunity to really pioneer something, then this could be the position for you. <br />
<br />
'''Key Responsibilities'''<br />
*Design and Develop our first NLG/NLP Application within Equities Research<br />
*Work closely with the vendor to understand the application limitations and functionality<br />
*Drive the development with the Head of Research as well as industry analysts<br />
*Mature the offering and look for further areas of development within the business<br />
<br />
'''About You'''<br />
<br />
To be successful in this role as a Software Engineer you will possess a University Degree in Computer Science/Mathematics and would have probably undertaken further studies of some sort (Masters/PhD) and have previous Natural Language Generation/Processing experience in either a commercial or research environment. You will have a passion and flair for the English Language as well as having a interest in financial services and in particular traded products. Previous OO Development experience would be highly regarded. In addition you will possess the following:<br />
<br />
*Tenacity to produce different If Statements and to develop the platform further<br />
*Strong interest in Artificial Intelligence/Machine Based Learning.<br />
*Keen interest in finance<br />
*Self Starter and strong attention to detail to really drive uptake of the platform<br />
<br />
This is a unique opportunity within Macquarie and quite possibly a pioneering project within the Investment Banking space. We are looking to hire two developers into the team and are flexible across career levels from recent Grads to Senior Engineers. Here at Macquarie we truly believe in you owning your future, at Macquarie you’ll own it. Find out more at the new Careers website: '''macquarie.com/career'''<br />
<br />
If you meet the above requirements, please apply via the following link. Alternatively to find out more about the position and a confidential discussion, please contact '''Andy Logan on 02 8237 8472 or andy.logan@macquarie.com'''<br />
<br />
== PostDoc Position in Heidelberg (NLP, Networks, Databases, Machine Learning)==<br />
*Employer: Heidelberg Institute for Theoretical Studies gGmbH (HITS)<br />
*Title: PostDoc<br />
*Specialties: Natural Language Processing, Networks, Databases, Machine Learning<br />
*Location: Heidelberg, Germany<br />
*Deadline: 20 February 2015<br />
*Date posted: 29 January 2015<br />
*Contact information: michael.strube (at) h-its.org<br />
*Online application: https://application.h-its.org/intern/register.php?id=o51kdq1<br />
<br />
'''Job Description'''<br />
PostDoc position available in the NLP group at the Heidelberg Institute for Theoretical Studies (HITS) in Heidelberg, Germany<br />
<br />
One position is available for a PostDoc working in Natural Language Processing, in particular in the areas of Entity Linking, Cross-document Coreference Resolution, Coreference Resolution, Word Sense Disambiguation. The position is within a newly funded project on "Scalable Author Name Disambiguation in Bibliographic Databases". Project partners are DBLP (http://dblp.org/db/) and zbMATH (https://zbmath.org/), the two leading bibliographic databases in computer science and mathematics which will also supply the data to be disambiguated and the gold standard. The project will be funded for three years starting June 1st, 2015.<br />
<br />
The candidate should have a strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science. Experience with machine learning, databases, parallel programming, big data and networks as well as strong programming skills are required.<br />
<br />
HITS gGmbH is a private non-profit research institute carrying out multidisciplinary research in the computational sciences. It receives its base funding from the HITS Stiftung.<br />
<br />
The NLP group (http://www.h-its.org/en/research/nlp/) at HITS is an interdisciplinary research group that works on applications in the area of discourse and dialogue, in particular coreference resolution, entity linking, automatic summarization, and knowledge extraction from semistructured input. The NLP group at HITS works closely together with the Computational Linguistics Department at the University of Heidelberg. <br />
<br />
To apply, please enter your application via the following link: https://application.h-its.org/intern/register.php?id=o51kdq1 (reference Postdoc NLP HITS-01-2015)<br />
<br />
Applications must be submitted by February 20, 2015. Please note that applications not submitted via the online system will not be considered. Inquiries about the position can be directed at Michael Strube (michael.strube (at) h-its.org).<br />
<br />
<br />
==Postdoc position in Cardiff (NLP, IR, machine learning)==<br />
*Employer: Cardiff University<br />
*Title: Postdoc<br />
*Specialties: Natural language processing, information retrieval, machine learning, distributional models, relation extraction, commonsense resoning<br />
*Location: Cardiff, UK<br />
*Deadline: 3 February 2015<br />
*Date posted: 9 January 2015<br />
*Contact information: SchockaertS1@cardiff.ac.uk<br />
<br />
'''Job Description'''<br />
<br />
Applications are invited for a postdoctoral research associate post in the School of Computer Science & Informatics at Cardiff University. This is a full-time, fixed-term post for 30 months, starting on 1 May 2015 or as soon as possible thereafter. <br />
<br />
The main aim of this project is to learn fine-grained semantic relations from large text corpora. Initially such relations will be obtained in an unsupervised way, by identifying semantic relations with spatial relations between vector-space representations. Subsequently, open-domain, supervised relation extraction methods will be developed which use the output of the unsupervised methods as training data. This research will be part of an ERC funded project on the use of semantic relations between natural language terms in logics for commonsense reasoning. You will work closely with Dr Steven Schockaert. You will possess a PhD in Computer Science or a closely related area, or have equivalent experience.<br />
<br />
'''Essential criteria'''<br />
<br />
*Proven ability to undertake research in a relevant research area (e.g. natural language processing, information retrieval, machine learning) at an international level, as evidenced by research output. <br />
*Excellent programming skills (java or C/C++). <br />
*A demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, SIGIR, CIKM, IJCAI, AAAI, ICML) and journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, ACM Trans. Information Systems, IEEE Trans. Knowledge and Data Engineering). <br />
*Proven ability to communicate specialist ideas clearly in English using written media. <br />
*Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme. <br />
*A PhD in Computer Science or closely related area, or equivalent experience.<br />
<br />
'''Desirable criteria'''<br />
<br />
*Knowledge of statistical natural language processing. <br />
*Knowledge of unsupervised and semi-supervised learning. <br />
*Knowledge of relation extraction. <br />
*Experience with analysing large text corpora using a high-performance computing environment. <br />
*Experience with dimensionality reduction methods such as multi-dimensional scaling, singular-value decomposition, and non-negative matrix factorisation.<br />
<br />
'''More information'''<br />
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 2972BR.<br />
<br />
==Post‐Doctoral and all levels of Research Scientist at the Allen Institute for Artificial Intelligence==<br />
*Employer: Allen Institute for Artificial Intelligence (AI2)<br />
*Title: Post-doc/Research Scientist<br />
*Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation<br />
*Location: Seattle, WA<br />
*Deadline: N/A, we are hiring throughout 2015<br />
*Date posted: 12/9/2014<br />
*Contact information: ai2-info@allenai.org, allenai.org<br />
<br />
'''Job Description'''<br />
<br />
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni. The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Post Docs and Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities. <br />
<br />
'''Position Summary'''<br />
<br />
AI2 currently has projects in the following areas:<br />
*Language and Vision<br />
*Information extraction and semantic parsing<br />
*Question answering<br />
*Language and reasoning<br />
*Machine learning and theory formation<br />
*Semantic search<br />
*Diagram understanding<br />
<br />
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission. These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting the research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations.<br />
<br />
'''Applicant'''<br />
<br />
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, or question answering and explanation. We look favorably upon extensive work experience demonstrating application of your research.<br />
<br />
'''Application Process'''<br />
<br />
All candidates are required to submit a resume, an expression of interest, and the names and contact information of at least 2 references (including email addresses) through our website: http://allenai.github.io/ai2website/jobs.html. We particularly welcome applications from women, people of color, members of the LGBT communities, and people with disabilities. Visa sponsorship is available.<br />
<br />
<br />
==Multiple Tenure-Track Positions (w/focus in Data Analytics) at The Ohio State University Department of Computer Science and Engineering==<br />
* Employer: The Ohio State University<br />
* Title: Assistant/Associate/Full Professor<br />
* Specialty: open, two positions in Data Analytics<br />
* Location: Columbus, OH, USA<br />
* Deadline: January 31, 2015 (Consideration starts November 2014)<br />
* Date Posted: November 17, 2014<br />
* Website: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi<br />
<br />
The Computer Science and Engineering Department at the Ohio State University expects to fill multiple tenure-track positions and seeks applicants in all areas of computer science.<br />
<br />
Particular emphasis will be placed on filling two open rank positions in conjunction with a broad university-wide research initiative on Data Analytics (https://discovery.osu.edu/focus-areas/data-analytics/collaborative.html), and a recently announced undergraduate program in Data Analytics (https://data-analytics.osu.edu). Areas of interest for these positions include (but are not limited to): data mining, big data management, cloud computing systems, data analytics; application of machine learning or data mining or data visualization to problems in network science (including social networks), health, and climate science.<br />
<br />
The department is committed to enhancing faculty diversity; women, minorities, and individuals with disabilities are especially encouraged to apply.<br />
<br />
Applicants should hold or be completing a Ph.D. in CSE or a closely related field, have a commitment to and demonstrated record of excellence in research, and a commitment to excellence in teaching.<br />
<br />
To apply, please submit your application via the online database. The link can be found at: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi.<br />
<br />
Review of applications will begin in November 2014 and will continue until the positions are filled.<br />
<br />
The Ohio State University is an Equal Opportunity/Affirmative Action Employer.</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Newsgroups,_mailing_lists&diff=10939Newsgroups, mailing lists2015-01-26T17:23:58Z<p>Tristan Miller: Strange that the list of newsgroups didn't contain any actual newsgroups until now... :)</p>
<hr />
<div><!-- Please keep this list in alphabetical order --><br />
* [http://www.cs.um.edu.mt/mailman/listinfo/sigsemitic ACL SIG on Computational Approaches to Semitic Languages]<br />
* [https://groups.google.com/a/datacommunitydc.org/forum/#!forum/nlp Data Community DC Natural Language Processing]<br />
* [http://www.meetup.com/DC-NLP/messages/archive/ DC NLP Meetup Group mailing list]<br />
* [http://tech.groups.yahoo.com/group/CAN-TAL-NLP/ CAN-TAL-NLP] - Canadian NLP<br />
* [news:comp.ai.nat-lang comp.ai.nat-lang] newsgroup<br />
* [http://torvald.aksis.uib.no/corpora/ Corpora List]<br />
* [http://sgi.nu/enron/mailinglist.php Enron Email Corpus Mailing List]<br />
* [https://cs.haifa.ac.il/mailman/listinfo/formalgrammar FG Mailing List] - Formal Grammar<br />
* [http://ling.ohio-state.edu/HPSG/Majordomo.html HPSG Mailing List] - Head-Driven Phrase Structure Grammar<br />
* [http://heim.ifi.uio.no/~dag/ling-tex.html Ling-TeX] - Typesetting linguistics material with TeX/LaTeX<br />
* [http://linguistlist.org/lists/index.html LINGUIST List]<br />
* [http://www.eamt.org/mt-list.html MT List] - Machine Translation<br />
* [http://mallet.cs.umass.edu/mailinglist.php MALLET software mailing list]<br />
* [http://listserv.linguistlist.org/archives/nsm-l.html Natural Semantic Metalanguage List]<br />
* [http://groups.google.com/group/nltk-users NLTK software mailing list]<br />
* [http://tech.groups.yahoo.com/group/Pashto-Urdu-Computational-Linguistics/ Pashto-Urdu] - Pashto-Urdu Computational Linguistics<br />
* [http://listserv.hum.gu.se/mailman/listinfo/senseval-discuss SENSEVAL discussion list] - word sense disambiguation<br />
* [http://tech.groups.yahoo.com/group/SentimentAI/ SentimentAI] - sentiment, opinions, and affect in text<br />
* [http://www.sigsem.org/wiki/Mailing_list SIGSEM] - mailing list on computational semantics<br />
* [http://www.siggen.org/mailing.html SIGGEN] - mailing list on natural language generation<br />
* [http://www.sigir.org/sigirlist/issues/ SIG-IRList Archives] - Information Retrieval<br />
* [https://mailman.stanford.edu/mailman/listinfo/java-nlp-user Stanford NLP software mailing list]<br />
* [http://tech.groups.yahoo.com/group/syntax/ Syntax] - linguistics, language, syntax, semantics, generative grammar, generative linguistics, formal grammar, minimalism<br />
* [http://tech.groups.yahoo.com/group/TextAnalytics/ Text Analytics]<br />
<br />
==Other lists of newsgroups and mailing lists==<br />
* [http://www.cs.technion.ac.il/~gabr/resources/news_mail.html Newsgroups and mailing lists for Text, Speech and Language Processing]<br />
<br />
==IRC channels==<br />
* #linguistics on irc.freenode.net (general and computational linguistics)<br />
* #nlp on irc.freenode.net (computational linguistics)<br />
<br />
==See also==<br />
* [[List of resources by language]]<br />
* [[Special interest groups]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Word_sense_disambiguation_resources&diff=10920Word sense disambiguation resources2014-12-12T11:42:57Z<p>Tristan Miller: migrated from https://www.ukp.tu-darmstadt.de/research/scientific-community/ukpedia/word-sense-disambiguation/</p>
<hr />
<div>[[Word sense disambiguation]] (WSD) is an open problem in natural language processing concerned with determining which sense (i.e., meaning) of a word is used in a particular context. This article provides provides links to important WSD-related publications, software, corpora, and other resources.<br />
<br />
==Introductory material, overviews, and surveys==<br />
* [http://en.wikipedia.org/wiki/Word_sense_disambiguation Word sense disambiguation] (Wikipedia)<br />
* [http://www.scholarpedia.org/article/Word_sense_disambiguation Word sense disambiguation] (Scholarpedia)<br />
* [http://aclweb.org/aclwiki/index.php?title=Word_sense_disambiguation Word sense disambiguation] (ACLWiki)<br />
* Eneko Agirre and Philip Edmonds, editors. [http://www.wsdbook.org/ ''Word Sense Disambiguation: Algorithms and Applications''], volume 33 of Text, Speech, and Language Technology. Springer, 2006. ISBN 978-1-4020-6870-6.<br />
* [http://www.d.umn.edu/%7Etpederse/WSDTutorial.html Advances in Word Sense Disambiguation tutorial] by Rada Mihalcea and Ted Pedersen (2005)<br />
* Roberto Navigli. [http://dl.acm.org/citation.cfm?doid=1459352.1459355 Word sense disambiguation: A survey]. ''ACM Computing Surveys'', 41:10:1–10:69, February 2009. ISSN 0360-0300.<br />
* Nancy Ide and Jean Véronis. [http://www.up.univ-mrs.fr/%7Everonis/pdf/1998wsd.pdf Introduction to the special issue on word sense disambiguation: The state of the art]. ''Computational Linguistics'', 24(1):1–40, 1998. ISSN 0891-2017.<br />
* K. C. Litkowski. Computational lexicons and dictionaries. In Keith Brown, editor, ''Encyclopedia of Language and Linguistics'', pages 753–761. Elsevier Science, Oxford, second edition, 2005. ISBN 978-0-08-044299-0.<br />
* Philip Edmonds. Lexical disambiguation. In Keith Brown, editor, ''Encyclopedia of Language and Linguistics'', pages 607–623. Elsevier Science, Oxford, second edition, 2005. ISBN 978-0-08-044299-0.<br />
* David Jurafsky and James H. Martin. ''Speech and Language Processing'', chapter Computational Lexical Semantics. Prentice Hall, second edition, 2008. ISBN 978-0131873216.<br />
* Christopher D. Manning and Hinrich Schütze. ''Foundations of Statistical Natural Language Processing'', chapter Word Sense Disambiguation, pages 229–264. The MIT Press, 1999. ISBN 978-0262133609.<br />
* David Yarowsky. Word sense disambiguation. In Nitin Indurkhya and Fred J. Damerau, editors, ''Handbook of Natural Language Processing'', pages 315–338. Chapman and Hall/CRC, second edition, 2010. ISBN 978-1420085921.<br />
<br />
==Conferences, workshops, and journals==<br />
* [http://www.dcs.shef.ac.uk/research/ilash/iccl/ The International Committee on Computational Linguistics (ICCL)] and its conferences:<br />
** [http://www.dcs.shef.ac.uk/research/ilash/iccl/ International Conference on Computational Linguistics (COLING)]<br />
* [http://www.aclweb.org/ The Association for Computational Linguistics (ACL)] and its associated organizations, conferences, workshops, and special interest groups:<br />
** [http://www.clres.com/siglex.html ACL SIGLEX], the umbrella organization for the [http://www.senseval.org/ Semeval and Senseval] evaluation exercises:<br />
*** [http://www.itri.brighton.ac.uk/events/senseval/ARCHIVE/index.html Senseval-1] (1998)<br />
*** [http://www.sle.sharp.co.uk/senseval2 Senseval-2] (2001)<br />
*** [http://www.senseval.org/senseval3 Senseval-3] (2004)<br />
*** [http://nlp.cs.swarthmore.edu/semeval Semeval-1] (2007)<br />
*** [http://semeval2.fbk.eu/ Semeval-2] (2010)<br />
*** [http://www.cs.york.ac.uk/semeval/ Semeval-3] (2013)<br />
* [http://ixa2.si.ehu.es/clirwsd/ Robust WSD task] at the [http://clef-campaign.org/ Cross Language Evaluation Form (CLEF)]<br />
* [http://www.mitpressjournals.org/loi/coli ''Computational Linguistics'']. MIT Press. ISSN 0891-2017.<br />
** [http://www.aclweb.org/anthology-new/J/J98/ ''Computational Linguistics'', 24(1), 1998. Special issue on word sense disambiguation].<br />
* [http://journals.cambridge.org/action/displayJournal?jid=NLE ''Natural Language Engineering'']. Cambridge University Press. ISSN 1351-3249.<br />
**[http://journals.cambridge.org/action/displayIssue?decade=2000&jid=NLE&volumeId=8&issueId=04&iid=138358 ''Natural Language Engineering'', 8(4), 2002. Special issue on evaluating word sense disambiguation systems].<br />
<br />
==Sense inventories and other lexical resources==<br />
; [http://www.webdante.com/ DANTE]<br />
: A lexical database for English<br />
; [http://www.ibiblio.org/webster/ GCIDE_XML]<br />
: The GNU version of the ''Collaborative International Dictionary of English'' (CIDE), presented in XML<br />
; [http://www.itri.brighton.ac.uk/events/senseval/ARCHIVE/resources.html#lex HECTOR]<br />
: A 35-word English dictionary used for Senseval-1<br />
; ''Longman Dictionary of Contemporary English'' (LDOCE). Burnt Mill, Essex: Longman, 1978<br />
: This proprietary dictionary saw considerable use by the WSD research community before less restrictively licensed resources became available.<br />
; ''Roget's International Thesaurus''. New York: Harper Collins, 1992<br />
: This proprietary thesaurus saw considerable use by the WSD research community before less restrictively licensed resources became available.<br />
; [http://rogets.site.uottawa.ca/ The Open Roget's Project]<br />
: A free implementation of the 1911 ''Roget's Thesaurus''.<br />
===Wordnets and associated resources===<br />
;[http://wordnet.princeton.edu/ WordNet]<br />
: A lexical database for English<br />
; [http://www.globalwordnet.org/gwa/wordnet_table.htm Wordnets in the world]<br />
: A list of wordnets for various languages<br />
; [http://xwn.hlt.utdallas.edu/ eXtended WordNet]<br />
: A version of WordNet where the glosses are syntactically parsed, transformed into logic forms, and content words are semantically disambiguated <br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#wordnet Inter-version WordNet mappings]<br />
: Mapping between synsets offsets in various WordNet versions<br />
; [http://www.lsi.upc.edu/~nlp/meaning/downloads.html MCR]<br />
: An integration of five local wordnets, the EuroWordNet Top Concept ontology, MultiWordNet Domains, and hundreds of thousands of new semantic relations and properties automatically acquired from corpora.<br />
<br />
==Annotated corpora==<br />
; [http://www.computing.dcu.ie/%7Easmeaton/SIGIR96-captions/ Alan Smeaton and Ian Quigley's image captions]<br />
: 8816 WordNet 1.5-annotated instances of 2304 lemmas in 2714 image captions<br />
; [http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC97T12 DSO Corpus of Sense-Tagged English]<br />
: Sense-tagged word occurrences for 121 nouns and 70 verbs occurring in the Brown Corpus and ''Wall Street Journal'' corpus<br />
; [http://www.itri.brighton.ac.uk/events/senseval/ARCHIVE/resources.html HECTOR (Senseval-1)]<br />
: Separate training and test corpora with 35 word types annotated with their HECTOR senses. See also Ted Pedersen's conversions.<br />
; interest<br />
: ''Wall Street Journal'' articles with 2369 instances of "interest" annotated with their LDOCE senses. See Ted Pedersen's conversions.<br />
; line, hard, serve<br />
: ''Wall Street Journal'' articles with over 12,000 instances of "line", "hard", and "serve" tagged with a subset of their WordNet 1.5 senses. See Ted Pedersen's conversions.<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#omwe Open Mind Word Expert sense-tagged data]<br />
: Various data sets for English, Romanian, and Hindi<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#sensevalsemcor Rada Mihalcea's Senseval-2 and Senseval-3 conversions into SemCor format]<br />
: Senseval-2 and Senseval-3 English all-words data converted into SemCor format<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#semcor SemCor]<br />
: Brown Corpus texts annotated with WordNet 1.6 senses, and automatically mapped to WordNet 1.7, WordNet 1.7.1, WordNet 2.0, WordNet 2.1, WordNet 3.0<br />
; [http://www.grsampson.net/Resources.html SEMiSUSANNE]<br />
: 33 sense-tagged and structurally annotated documents from the Brown Corpus<br />
; [http://ixa.si.ehu.es/Ixa/resources/sensecorpus Sensecorpus]<br />
: Automatically extracted examples for all WordNet 1.6 noun senses and topic signatures built based on those examples<br />
; [http://86.188.143.199/senseval2/Results/guidelines.htm#rawdata Senseval-2]<br />
: Three all-words sense-annotated Penn Treebank II articles comprising in total some 5000 words of running text, plus some Penn Treebank II ''Wall Street Journal'' and British National Corpus text where 75 to 300 instances of a total of 73 nouns, adjectives, and verbs have been annotated with their WordNet 1.7 senses. See also Ted Pedersen's and Rada Mihalcea's conversions.<br />
; [http://www.d.umn.edu/%7Etpederse/data.html Ted Pederson's Sense-tagged Text]<br />
: Versions of the Senseval-1, Senseval-2, line, hard, serve, and interest data which have been converted to a common format (Senseval-2), POS tagged, and parsed.<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#twa TWA sense-tagged data]<br />
: Sense tagged data for six words with two-way ambiguities (bass, crane, motion, palm, plant, tank)<br />
; [http://wordnet.princeton.edu/glosstag.shtml WordNet Gloss Disambiguation Project]<br />
: A corpus of WordNet 3.0 glosses with word forms disambiguated to their WordNet 3.0 senses<br />
<br />
==Software==<br />
; [http://sourceforge.net/projects/cuitools/ CuiTools]<br />
: A complete word sense disambiguation system that assigns senses to biomedical text based on the UMLS<br />
; [https://code.google.com/p/dkpro-wsd/ DKPro WSD]<br />
: A collection of software components for word sense disambiguation based on the Apache UIMA framework.<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#gwsd GWSD: Unsupervised Graph-based Word Sense Disambiguation]<br />
: A system for unsupervised all-words graph-based word sense disambiguation<br />
; [http://alias-i.com/lingpipe/ LingPipe]<br />
: A Java natural language processing toolkit. A [http://alias-i.com/lingpipe/demos/tutorial/wordSense/read-me.html tutorial on using LingPipe for word sense disambiguation] is available.<br />
; [http://www.nltk.org/ Natural Language Toolkit (NLTK)]<br />
: Python modules for NLP, including a module for reading Senseval-2 data<br />
; [http://www.d.umn.edu/%7Etpederse/senseclusters.html SenseClusters]<br />
: A package of (mostly) Perl programs that allows a user to cluster similar contexts together using unsupervised knowledge-lean methods.<br />
; [http://www.cse.unt.edu/%7Erada/downloads.html#senselearner SenseLearner]<br />
: An all-words word sense disambiguation tool<br />
; [http://www.d.umn.edu/%7Etpederse/sensetools.html SenseTools]<br />
: A suite of tools that allow for easy creation of supervised word sense disambiguation<br />
; [http://www.d.umn.edu/%7Etpederse/tools.html Senseval-2 data format converters]<br />
: Tools to convert between the following formats: Senseval-1, Senseval-2, Senseval-2 with conflated words, Headless Senseval-2, WePS, English Giga Word, plain text, National Library of Medicine Test Collection, Open Mind Data<br />
; [http://senserelate.sourceforge.net/ WordNet::SenseRelate]<br />
: Perl tools which use measures of semantic similarity and relatedness to perform word sense disambiguation<br />
; [http://sourceforge.net/projects/wsdgate/ WSD Gate]<br />
: A word sense disambiguation toolkit using GATE and WEKA<br />
; [http://www.d.umn.edu/%7Etpederse/wsdshell.html WSD Shell]<br />
: An improved version of the Duluth-Shell which was used as a driver for the Duluth Senseval-2 and Senseval-3 systems</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Word_sense_disambiguation&diff=10919Word sense disambiguation2014-12-12T11:21:51Z<p>Tristan Miller: /* See also */ * Word sense disambiguation resources</p>
<hr />
<div>'''Word Sense Disambiguation''' (WSD) is the process of identifying the sense of a polysemic word.<br />
<br />
In modern WSD systems, the senses of a word are typically taken from some specified dictionary. These days [[WordNet]] is the usual dictionary in question. WSD has been investigated in computational linguistics as a specific task for well over 40 years, though the acronym is newer. The SENSEVAL conferences have attempted to put Word Sense Disambiguation on an empirically measurable basis by hosting evaluations in which a given corpus of tagged word senses are created using [[WordNet]]'s senses and participants attempt to recognize those senses after tuning their systems with a corpus of training data.<br />
<br />
==Introduction==<br />
One of the first problems that is encountered by any natural language processing system is that of lexical ambiguity, be it syntactic or semantic. The resolution of a word's syntactic ambiguity has largely been solved in language processing by part-of-speech taggers which predict the syntactic category of words in text with high levels of accuracy. <ref>E. Brill. Transformation-based error-driven learning and natural language processing: A case study in part of speech tagging. Computational Linguistics, 21(4):543-566, December 1995</ref><br />
The problem is that words often have more than one meaning, sometimes fairly similar and sometimes completely different. The meaning of a word in a particular usage can only be determined by examining its context. This is, in general, a trivial task for the human language processing system, for example consider the following two sentences, each with a different sense of the word bank :<br />
#The boy leapt from the bank into the cold water. <br />
#The van pulled up outside the bank and three masked men got out. <br />
We immediately recognise that in the first sentence bank refers to the edge of a river and in the second to a building. However, the task has proved to be difficult for computer and some have believed that it would never be solved. An early sceptic was Bar-Hillel who famously proclaimed that "sense ambiguity could not be resolved by electronic computer either current or imaginable". <ref>Y. Bar-Hillel. Language and Information. Addison-Wesley, 1964.</ref><br />
However, the situation is not as bad as Bar-Hillel feared, there have been several advances in word sense disambiguation and it is now at a stage where lexical ambiguity in text can be resolved with a reasonable degree of accuracy.<br />
<br />
==History==<br />
The problem of WSD was first introduced by Warren Weaver in 1949 <ref>W. Weaver. 1949. [http://www.hutchinsweb.me.uk/MTNI-22-1999.pdf Translation]. In Machine Translation of Languages: Fourteen Essays, ed. by Locke, W.N. and Booth, A.D. Cambridge, MA: MIT Press.</ref>. In 1975 Kelly and Stone <ref>E.F. Kelly and P.J. Stone. 1975. Computer Recognition of English Word Senses, Amsterdam: North-Holland.</ref> published a book explicitly listing their rules for disambiguation of word senses. As large-scale lexical resources became available in the 1980s, the automatic extraction of lexical knowledge became possible, disambiguation was still knowledge- or dictionary - based though. With the rise of statistical methods in CL in the 1990s, WSD became one of the main focus' of supervised learning techniques.<br />
<br />
==Approaches==<br />
===Knowledge based===<br />
Under this approach disambiguation is carried out using information from an explicit lexicon or knowledge base. The lexicon may be a machine readable dictionary, thesaurus or it may be hand-crafted. This is one of most popular approaches to word sense disambiguation and amongst others, work has been done using existing lexical knowledge sources such as WordNet <ref>Agirre, E. and Rigau, G. (1996). Word sense disambiguation using conceptual density. In Proceedings of COLING'96</ref> and LDOCE <ref>J. Guthrie, L. Guthrie, Y. Wilks and H. Aidinejad, Subject-Dependent Co-Occurrence and Word Sense Disambiguation, ACL-91, pp. 146-152.</ref>.<br />
The information in these resources has been used in several ways, for example Wilks and Stevenson <ref>Y. Wilks and M. Stevenson. The Grammar of Sense: using part-of-speech tags as a first step in semantic disambiguation. To appear in Journal of Natural Language Engineering, 4(3).</ref> use large lexicons (generally machine readable dictionaries) and the information associated with the senses (such as part-of-speech tags, topical guides and selectional preferences) to indicate the correct sense. Another approach is to treat the text as an unordered bag of words where similarity measures are calculated by looking at the semantic similarity (as measured from the knowledge source) between all the words in the window regardless of their positions, as was used by Yarowsky <ref>D. Yarowsky. Word-sense disambiguation using statistical models of Roget's categories trained on large corpora. In Proceedings of the 14th International Conference on Computational Linguistics (COLING-92), pages 454-460, Nantes, France, 1992.</ref>.<br />
===Corpus based===<br />
This approach attempts to disambiguate words using information which is gained by training on some corpus, rather that taking it directly from an explicit knowledge source. This training can be carried out on either a disambiguated or raw corpus, where a disambiguated corpus is one where the semantics of each polysemous lexical item is marked and a raw corpus one without such marking.<br />
====Disambiguated corpora====<br />
This set of techniques requires a training corpus which has already been disambiguated. In general a machine learning algorithm of some kind is applied to certain features extracted from the corpus and used to form a representation of each of the senses. This representation can then be applied to new instances in order to disambiguate them. Different researchers have made use of different sets of features, for example local collocates such as first noun to the left and right, second word to the left/right and so on. However, a more common feature set is to take all the words in a window of words around the ambiguous words, treating the context as an unordered bag of words.<br />
Another approach is to use Hidden Markov Models which have proved very successful in part-of-speech tagging. Realizing of course that semantic tagging is a much more difficult problem than part-of-speech tagging, <ref>Segond, F., Schiller, A., Grefenstette, G., and Chanod, J. (1997). An experiment in semantic tagging using hidden markov model tagging. In Vossen, P., Adriaens, G., Calzolari, N., Sanfilippo, A., and Wilks, Y., editors, Proceedings of the ACL/EACL'97 Workshop on Automatic Information Extraction and Building of Lexical Semantic Resources.</ref> decided nonetheless to perform an experiment to see how well words can be semantically disambiguated using techniques that have proven to be effective in part-of-speech tagging. This experiment involved the following steps:<br />
#deriving a lexicon from the WordNet data files which contains all possible semantic tags for each noun, adjective, adverb and verb. Words having no semantic tags (determiners, prepositions, auxiliary verbs, etc.) are ignored.<br />
#constructing a training corpus and a test corpus from the semantically tagged Brown corpus (manually tagged by the WordNet team) by extracting tokens for the HMM bigrams.<br />
#computing a HMM model based on the training corpus, runnig the tagger on the test corpus and comparing the results with the original tags in the test corpus.<br />
The general problem with these methods is their reliance on disambiguated corpora which are expensive and difficult to obtain. This has meant that many of these algorithms have been tested on very small numbers of different words, often as few as 10.<br />
====Raw Corpora====<br />
It is often difficult to obtain appropriate lexical resources (especially for texts in a specialized sublanguage). This lack of resources has led several researchers to explore the use of unannotated, raw, corpora to perform unsupervised disambiguation. It should be noted that unsupervised disambiguation cannot actually label specific terms as a referring to a specific concept: that would require more information than is available. What unsupervised disambiguation can achieve is word sense discrimination, it clusters the instances of a word into distinct categories without giving those categories labels from a lexicon (such as WordNet synsets).<br />
An example of this is the dynamic matching technique<ref>Radford et al. (1996)</ref> which examines all instances of a given term in a corpus and compares the contexts in which they occur for common words and syntactic patterns. A similarity matrix is thus formed which is subject to cluster analysis to determine groups of semantically related instances of terms.<br />
Another example is the work of Pedersen <ref>T. Pedersen and R. Bruce. Distinguishing word senses in untagged text. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, Providence, RI, August 1997.</ref> who compared three different unsupervised learning algorithms on 13 different words. Each algorithm was trained on text with was tagged with either the WordNet or LDOCE sense for the word but the algorithm had no access to the truce senses. What it did have access to was the number of senses for each word and each algorithm split the instances of each word into the appropriate number of clusters. These clusters were then mapped onto the closest sense from the appropriate lexicon. Unfortunately the results are not very encouraging, Pedersen reports 65-66% correct disambiguation depending on the learning algorithm used. This result should be compared against that fact that, in the corpus he used, 73% of the instances could be correctly classified by simply choosing the most frequent sense.<br />
===Hybrid Approaches===<br />
These approaches can be neither properly classified as knowledge or corpus based but use part of both approaches. A good example of this is Luk's system <ref>A. Luk. Statistical sense disambiguation with relatively small corpora using dictionary definitions. In Proceedings of the 33rd Meetings of the Association for Computational Linguistics (ACL-95), pages 181-188, Cambridge, M.A., 1995.</ref> which uses the textual definitions of senses from a machine readable dictionary (LDOCE) to identify relations between senses. He then uses a corpus to calculate mutual information scores between these related senses in order to discover the most useful. This allowed Luk to produce a system which used the information in lexical resources as a way of reducing the amount of text needed in the training corpus.<br />
Another example of this approach is the unsupervised algorithm of Yarowsky <ref>D. Yarowsky. Unsupervised word-sense disambiguation rivaling supervised methods. In Proceedings of the 33rd Annual Meeting of the Association for Computational Lainguistics (ACL '95), pages 189-196, Cambridge, MA, 1995.</ref>. This takes a small number of seed definitions of the senses of some word (the seeds could be WordNet synsets or definitions from some lexicon) and uses these to classify the "obvious" cases in a corpus. Decision lists <ref>R. Rivest. Learning decision lists. Machine Learning, 2(3):229-246, 1987</ref> are then used to make generalisations based on the corpus instances classified so far and these lists are then re-applied to the corpus to classify more instances. The learning proceeds in this way until all corpus instances are classified. Yarowsky reports that the system correctly classifies senses 96% of the time.<br />
<br />
==Discussions==<br />
Word Sense Disambiguation has several debates within the field as to whether the senses offered in existing dictionaries are adequate to distinguish the subtle meanings used in text contexts and how to evaluate the overall performance of a WSD system. For example, does it make sense to describe an overall percentage accuracy for a WSD system or does evaluation require specific comparison of system performance on a word by word basis. <br />
<br />
== See also ==<br />
* [[Word Sense Disambiguation (State of the art)]]<br />
* [[Word sense disambiguation resources]]<br />
<br />
== External links ==<br />
<br />
* [http://en.wikipedia.org/wiki/Word_sense_disambiguation Wikipedia's introduction to WSD]<br />
* [http://www.scholarpedia.org/article/Word_sense_disambiguation Word sense disambiguation in Scholarpedia]<br />
<br />
==References==<br />
<references /><br />
<br />
<br />
[[Category:Word sense disambiguation|*]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Uncategorized_software&diff=10354Uncategorized software2013-10-16T07:55:45Z<p>Tristan Miller: remove entries already categorized</p>
<hr />
<div><div class="usermessage"><br />
* Please ''do not add anything new to this list''; we would like to eventually eliminate this list.<br />
* Please help us by moving links into categories; add new categories to [[Tools and Software]] if needed.<br />
* Please add new items to the [[List of resources by language]] where appropriate.<br />
</div><br />
<br />
==[[Software]] - Uncategorized and miscellaneous==<br />
<br />
*[http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/bookcode/allen/0.html Code from James Allen's "Natural Language Understanding" (code at CMU)]<br />
*[http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/bookcode/nlp_pp/0.html Code from Michael Covington's "NLP for Prolog Programmers" (code at CMU)]<br />
*[http://www.dtreg.com/ DTREG decision tree generator]<br />
*[http://homepage.mac.com/bncweb/home.html BNCweb: A Web-Based Interface to the British National Corpus] <br />
*[http://nlg18.csie.ntu.edu.tw:8080/opinion/index.html Chinese sentiment dictionary NTUSD] <br />
*[http://www.athel.com/colloc.html Collocate] <br />
*[http://lingo.stanford.edu/ CSLI LinGO Lab (Stanford)] <br />
*[http://www.lsi.upc.es/~nlp/freeling/ FreeLing 1.1] <br />
*[http://www.webir.org/resources.html IR and IE on the web] <br />
*[http://www.comp.nus.edu.sg/~qiul/NLPTools/JavaRAP.html JavaRAP] <br />
*[https://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library)] <br />
*[http://www.linguastream.org LinguaStream]<br />
*[http://xlex.uni-muenster.de/ MTP Xlex/www] <br />
*[http://www.langsoft.ch Natural Language Processing software] <br />
*http://opennlp.sf.net OpenNLP]<br />
*[http://www.dcs.shef.ac.uk/~francois/personality/recognizer.html Personality Recognizer from Text]<br />
*[http://www.nzdl.org/ELKB/ Roget's Thesaurus as an Electronic Lexical Knowledge Base] <br />
*[http://www.chass.utoronto.ca/tact/ Text Analysis Computing Tools (TACT)] <br />
*[http://odur.let.rug.nl/~vannoord/TextCat/ TextCat] <br />
*[http://igm.univ-mlv.fr/~unitex/ Unitex] <br />
*[http://www.mith2.umd.edu/products/ver-mach/ Versioning Machine 2.0]<br />
<br />
==Applications==<br />
<!-- Please keep this list in alphabetical order --><br />
<br />
<br />
*[http://webdeptos.uma.es/filifa/personal/amoreno/indexer/ BNC Indexer]<br />
*[http://www.brainhat.com/ Brainhat Natural Language Processing]<br />
*[http://www.chilibot.net/ Chilibot: NLP based miner for gene/protein/keyword relationships]<br />
*[http://www.bultreebank.org/clark CLaRK System]<br />
*[http://delphesintl.com/ Delphes Technologies International]<br />
*[http://www.dtreg.com DTREG 2.0 decision trees with TreeBoost]<br />
*[http://www.dfki.de/lt/registry/apps/korek21.html KOREKTOR 2.0 (at the DFKI NLP archive)]<br />
*[http://www.xs4all.nl/~bsarempt/linguistics/index.html KURA 1.0]<br />
*[http://ngram.sourceforge.net Ngram Statistics Package], identify collocations<br />
*[http://www.ccs.neu.edu/home/futrelle/bionlp/commercial/opus.html Opus, a commercial biology text mining system]<br />
*[http://sourceforge.net/projects/pytalk/ Project: Pytalk]<br />
*[http://www.wagsoft.com/RSTTool/ Release of RSTTool: RSTTool 2.7]<br />
*[http://senseclusters.sourceforge.net SenseClusters], cluster similar contexts<br />
*[http://www.softissimo.com/ SOFTISSIMO]<br />
*[http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html TreeTagger]<br />
<br />
==Tools==<br />
<br />
*[http://www.ldc.upenn.edu/Projects/ACE/Tools/ Automatic Content Extraction (ACE): Annotation Tools]<br />
*[http://www.norvig.com/paip/grammar.lisp a simple grammar of English]<br />
*[http://sourceforge.net/projects/acopost/ ACOPOST]<br />
*[http://acdc.linguateca.pt/example_alignment.html Alignment of bilingual corpora performed with EasyAlign]<br />
*[http://www.lsi.upc.es/~lambert/software/AlignmentSet.html Alignment Set Toolkit]<br />
*[http://lucene.apache.org/java/docs/ Apache Lucene]<br />
*[http://www.arabeyes.org/ Arabeyes Project]<br />
*[http://misshoover.si.umich.edu/~zzheng/sentence/ Automatic English Sentence Segmentation]<br />
*[http://www.clg.wlv.ac.uk/projects/CAST/demos.php Automatic Summarization Demos]<br />
*[http://www.r.dl.itc.u-tokyo.ac.jp/~nakagawa/resource/termext/atr-e.html Automatic Term Extraction System]<br />
*[http://lael.pucsp.br/corpora/ Bancos de dados e Ferramentas de an`alise]<br />
*[http://www.ai.mit.edu/~murphyk/Software/BNT/bnt.html Bayes Net Toolbox for Matlab]<br />
*[http://bndev.sourceforge.net/ Bayesian Network tools in Java (BNJ)]<br />
*[http://sslmit.unibo.it/~baroni/bootcat.html BootCaT: Simple Utilities to Bootstrap Corpora and Terms from the Web]<br />
*[http://callisto.mitre.org/ Callisto Annotation Tool]<br />
*[http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T13 CCGBank]<br />
*[http://lael.pucsp.br/corpora/alinhador/ CEPRIL aligner]<br />
*[http://pie.usna.edu/explorec.html Chargrams Database from British National Corpus]<br />
*[http://www.bultreebank.org/clark/index.html CLaRK System]<br />
*[http://dlt4.mit.edu/~dr/COALS/ COALS: Correlated Occurrence Analogue to Lexical Semantics]<br />
*[ftp://cs.nyu.edu/pub/html/comlex.html/ Comlex]<br />
*[http://www.ai.mit.edu/projects/iiip/doc/cl-http/home-page.html Common Lisp Hypermedia Server]<br />
*[http://www.cpan.org/ Comprehensive Perl Archive Network]<br />
*[http://clg.wlv.ac.uk/projects/CAST/ Computer Aided Summarisation Tool (CAST)]<br />
*[http://infomap.stanford.edu/webdemo Concept Search Engine Information Mapping Demo (Center for the Study of Language and Information, Stanford University)]<br />
*[https://sourceforge.net/projects/concollate/ Concollate]<br />
*[http://borel.slu.edu/crubadan/ Corpus building for minority languages]<br />
*[http://montev.isi.edu:8000/align-tool/?CORPUS=de-news-morphix&AFILE=full-model1-50-50.gz Corpus De-News-Morphix Alignment Tool]<br />
*[http://search.cpan.org/dist/SuffixTree/ CPAN Suffix Tree Module]<br />
*[http://www.ucl.ac.uk/english-usage/diachronic/index.htm Creating a Parsed and Searchable Diachronic Corpus of Present-Day Spoken English]<br />
*[http://www.cis.upenn.edu/~dbikel/software.html#wn Dan Bikel's Java WordNet Library]<br />
*[http://www.dataharmony.com/ Data Harmony, Document Management Software]<br />
*[http://www.cs.ualberta.ca/~lindek/demos.htm Demos of dependency database, parser, and other tools]<br />
*[http://fuzzy.cs.uni-magdeburg.de/~borgelt/dtree.html Dtree - Decision and Regression Tree Induction]<br />
*[http://www.foreignword.com/dictionary/truespel/transpel.htm English-Truespel (USA Accent) Text Conversion Tool]<br />
*[http://www.cs.jhu.edu/~brill/ Eric Brill's Part of Speech Tagger]<br />
*[http://odur.let.rug.nl/~vannoord/Fsa/Manual/node1.html Finite State Automata Utilities v6]<br />
*[http://www.jaist.ac.jp/~hieuxuan/flexcrfs/flexcrfs.html FlexCRFs: Flexible Conditional Random Fields]<br />
*[http://garraf.epsevg.upc.es/freeling/ FreeLing 1.2]<br />
*[http://grid.let.rug.nl/~vannoord/Fsa/fsa.html FSA6.2xx: Finite State Automata Utilities]<br />
*[http://gate.ac.uk/ GATE (General Architecture for Text Engineering)]<br />
*[http://www.clsp.jhu.edu/ws2005/groups/statistical/GenPar.html GenPar Toolkit for Generalized Parsing]<br />
*[http://www.parc.xerox.com/istl/groups/nltt/medley/ Grammar Writer's Workbench for Lexical Functional Grammar]<br />
*[http://heartofgold.dfki.de Heart of Gold - XML-based middleware for the integration of (deep and shallow) NLP components]<br />
*[http://htk.eng.cam.ac.uk Hidden Markov Model Toolkit]<br />
*[http://www.ida.liu.se/~nlplab/ILink/ I*Link]<br />
*[http://www.kbsim.com/ifind.html iFind KBSim.com - Knowledge-Based Simulations, Inc.]<br />
*[http://www.infogistics.com/posdemo.htm Infogistics: NLProcessor Interactive Demo]<br />
*[http://www.isi.edu/~marcu/software.html ISI's version of the RSTTool]<br />
*[http://www-2.cs.cmu.edu/~javabayes/Home/ JavaBayes - v0.346]<br />
*[http://www.dcs.shef.ac.uk/~francois/jmrc/index.html jMRC - MRC Psycholinguistic Database Java Interface]<br />
*[http://www.comp.leeds.ac.uk/andyr/software/jTokeniser/ jTokeniser]<br />
*[http://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library)]<br />
*[http://sslmit.unibo.it/%7ebaroni/welcome_to_knorpora.html Knorpora 1.0]<br />
*[http://miniappolis.com/KWiCFinder/KWiCFinderHome.html KWiCFinder]<br />
*[http://www.kwicfinder.com/KWiCFinder.html Kwicfinder]<br />
*[http://odur.let.rug.nl/~vannoord/TextCat/competitors.html Language Identification Tools]<br />
*[http://www-2.cs.cmu.edu/~lemur/download.html Lemur Toolkit Download]<br />
*[http://www.lemurproject.org/ Lemur Toolkit Website]<br />
*[http://www.leximancer.com/ Leximancer]<br />
*[http://www.csie.ntu.edu.tw/~cjlin/libsvm/ LIBSVM: A Library for Support Vector Machines]<br />
*[http://search.cpan.org/~lgoddard/Lingua-Syllable-0.03/Syllable.pm Lingua-Syllable]<br />
*[http://listserv.linguistlist.org/cgi-bin/wa?A2=ind0109&L=corpora&P=R729 list of POS taggers]<br />
*[http://ucrel.lancs.ac.uk/llwizard.html Log-likelihood calculator]<br />
*[ftp://ftp.ncbi.nlm.nih.gov/pub/lsmith/MedPost/medpost.tar.gz MedPost: A Part-of-Speech Tagger for BioMedical text]<br />
*[http://www.lexically.net/wordsmith/version4/index.htm Mike Scott's Web - Wordsmith Tools]<br />
*[http://mmax.eml-research.de MMAX Annotation Tool]<br />
*[http://www.dcs.shef.ac.uk/research/ilash/Moby/ Moby Database]<br />
*[http://search.cpan.org/author/SHLOMOY/Lingua-EN-Sentence-0.25/lib/Lingua/EN/Sentence.pm Module for splitting text into sentences]<br />
*[http://www.cs.berkeley.edu/~aiken/moss.html Moss: A System for Detecting Software Plagiarism]<br />
*[http://www.natlantech.com/lingbench_ide.html Natlanco]<br />
*[http://www.cs.jhu.edu/~brill/code.html Natural Language Processing Systems]<br />
*[http://www.ltg.ed.ac.uk/NITE/ NITE XML Toolkit]<br />
*[http://nltk.sourceforge.net NLTK - Natural Language Toolkit]<br />
*[http://crl.nmsu.edu/Tools/Software/ NMSU Natural Language Processing Tools]<br />
*[http://annotation.semanticweb.org/ontomat/index.html Ontomat Homepage]<br />
*[http://teach-computers.org/word-expert.html Open Mind]<br />
*[http://davinci.cs.ucdavis.edu/ OpenRCT Home]<br />
*[http://www.oriel.org/homonym.htm ORIEL -- Online Research Information Environment for the Life Sciences]<br />
*[http://clg.wlv.ac.uk/projects/PALinkA/ PALinkA: A Resource Annotation Tool]<br />
*[http://www.sil.org/ PC-KIMMO, Englex, PC-PATR, and PC-PARSE]<br />
*[http://wall.jussieu.fr/dyn/Context2 perl concordancer]<br />
*[http://www.tartarus.org/~martin/PorterStemmer/index.html Porter Stemming Algorithm]<br />
*[http://www.sciences.univ-nantes.fr/info/perso/permanents/enguehard/recherche/CoRRecT/CoRRecT_gb.htm Project CoRRecT: Reference Corpus for the Recognition of Terms]<br />
*[http://protege.stanford.edu/ Protege Project]<br />
*[http://www.lingsoft.fi/cgi-pub/engcg Publically available POS tagger]<br />
*[http://corpus.leeds.ac.uk/query-zh.html Query to Chinese Corpora]<br />
*[http://www-rali.iro.umontreal.ca/Reacc/ R&eacute;acc - reaccenting software]<br />
*[http://rdues.uce.ac.uk/acronym.shtml RDUES ACRONYM (Automatic Collocational Retrieval of NYMs) Project]<br />
*[http://www.comp.nus.edu.sg/~rpnlpir/daemonCollins/ README for the daemonized version of Collins' Parser]<br />
*[http://www.research-lab.com/ Research-lab.com]<br />
*[http://www.reitter-it-media.de/compling/index.html RST LaTeX (Reitter IT and Media)]<br />
*[http://herzberg.ca.sandia.gov/jess/index.shtml Rule Engine for the Java Platform]<br />
*[http://elib.cs.berkeley.edu/src/satz/ SATZ--Adaptive Sentence Boundary Detector]<br />
*[http://ixa.si.ehu.es/Ixa/resources/selprefs Selectional Preferences Extracted from Semcor for WordNet 1.6 Synsets (v 1.0)]<br />
*[http://ilk.uvt.nl/~sabine/chunklink/ Software - The chunklink script, by Sabine Buchholz]<br />
*[http://people.csail.mit.edu/people/mcollins/code.html Software and Data Sets for Collins Natural Language Parser]<br />
*[http://senta.di.ubi.pt Software for the Extraction of N-ary Textual Associations (SENTA)]<br />
*[http://www-a2k.is.tokushima-u.ac.jp/member/kita/NLP/nlp_tools.html Software Tools for NLP]<br />
*[http://sprout.dfki.de SProUT - Shallow Processing with Unification and Typed Feature Structures]<br />
*[http://www-nlp.stanford.edu/software/lex-parser.shtml Stanford Parser]<br />
*[http://www.lsi.upc.edu/%7Enlp/SVMTool/ SVMTool]<br />
*[http://swesum.nada.kth.se/index-eng.html SweSum - Automatic Text Summarizer (with PRM)]<br />
*[http://www.wagsoft.com/Coder/ Systemic Coder -- a Text Markup Tool (Version 4.5)]<br />
*[http://www-2.cs.cmu.edu/~lenzo/t2p/ t2p: Text-to-Phoneme Converter Builder]<br />
*[http://www.d.umn.edu/~tpederse/parallel.html Ted Pedersen - Tools for Parallel Text]<br />
*[http://lsi.research.telcordia.com/ Telcordia Latent Semantic Indexing Demo Machine]<br />
*[http://www.tei-c.org/Software/index.html Text Encoding Initiative --Tools]<br />
*[http://www.comp.lancs.ac.uk/computing/research/ucrel/claws/tagservice.html The CLAWS tagging service]<br />
*[http://www.clsp.jhu.edu/ws99/projects/mt/toolkit/ The EGYPT Statistical Machine Translation Toolkit]<br />
*[http://www.ims.uni-stuttgart.de/CorpusToolbox/ The IMS Corpus Toolbox Webpage]<br />
*[http://jazzy.sourceforge.net/ The Java Open Source Spell Checker]<br />
*[http://www.findingnames.net/ The Naming Company]<br />
*[http://timex2.mitre.org/taggers/timex2_taggers.html TIMEX2 Taggers]<br />
*[http://www.coli.uni-sb.de/~thorsten/tnt/ TnT - Statistical Part-of-Speech Tagger]<br />
*[http://www.cs.columbia.edu/nlp/tools.html Tools developed at Columbia University (FUF, Surge, Crep, Segmenter, Verber, Xtract)]<br />
*[http://www.torch.ch Torch3]<br />
*[http://main.amu.edu.pl/~sipkadan/lingo.htm Turbo Lingo]<br />
*[http://stp.ling.uu.se/cgi-bin/joerg/Uplug Uplug]<br />
*[http://wordlist.sourceforge.net/varcon-readme VarCon (Variant Conversion Info)]<br />
*[http://www.edict.com.hk/concordance/ Virtual Language Centre's Web Concordancer]<br />
*[http://www.textanalysis.com/ VisualText]<br />
*[http://sourceforge.net/projects/wordfreak Wordfreak]<br />
*[http://www.d.umn.edu/~tpederse/wsdshell.html WSD Shell]<br />
*[http://www.xml-ces.org/ XCES: Corpus Encoding Standard for XML]<br />
<br />
== WordNet stuff (placeholder) ==<br />
<br />
* [http://search.cpan.org/dist/WordNet-SenseRelate Word-Net SenseRelate]<br />
* [http://search.cpan.org/dist/WordNet-Similarity Word-Net Similarity]<br />
* [http://www.clres.com/WordNet.html alphabetic version of WordNet 2.0]<br />
* [http://www.ai.mit.edu/~jrennie/WordNet/ Perl interface to WordNet]<br />
<br />
== QA systems (placeholder, needs to go somewhere else) ==<br />
<br />
* [http://www.answerbus.com/index.shtml Answerbus -- Automatic Language Detection Software ]<br />
* [http://demos.inf.ed.ac.uk:8080/qualim/ QuALiM Question Answering System - Searches Wikipedia]<br />
* [http://start.csail.mit.edu/ START Natural Language Question Answering System]<br />
* [http://www.umiacs.umd.edu/~jimmylin/downloads/index.html Aranea Question Answering System]<br />
* [http://webglimpse.net/ Webglimpse]<br />
* [http://www.openchannelsoftware.org/projects/Qanda Qanda: Open source question answering system]<br />
<br />
==Miscellaneous==<br />
<br />
* [http://homepage.mac.com/bncweb/home.html BNCweb: A Web-Based Interface to the British National Corpus ]<br />
* [http://lingo.stanford.edu/ CSLI LinGO Lab (Stanford) ]<br />
* [http://nlg18.csie.ntu.edu.tw:8080/opinion/index.html Chinese sentiment dictionary NTUSD ]<br />
* [http://www.athel.com/colloc.html Collocate ]<br />
* [http://www.lsi.upc.es/~nlp/freeling/ FreeLing 1.1 ]<br />
* [http://www.webir.org/resources.html IR and IE on the web ]<br />
* [https://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library) ]<br />
* [http://www.comp.nus.edu.sg/~qiul/NLPTools/JavaRAP.html JavaRAP ]<br />
* [http://xlex.uni-muenster.de/ MTP Xlex/www ]<br />
* [http://www.langsoft.ch Natural Language Processing software ]<br />
* [http://www.dfki.de/lt/registry/draft.html Natural Language Software Registry (at DFKI) ]<br />
* [http://www.nzdl.org/ELKB/ Roget's Thesaurus as an Electronic Lexical Knowledge Base ]<br />
* [http://www.chass.utoronto.ca/tact/ Text Analysis Computing Tools (TACT) ]<br />
* [http://odur.let.rug.nl/~vannoord/TextCat/ TextCat ]<br />
* [http://igm.univ-mlv.fr/~unitex/ Unitex ]<br />
<br />
==See also==<br />
<br />
* [[Named entity recognizers]]<br />
<br />
[[Category:Software]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Uncategorized_software&diff=10353Uncategorized software2013-10-16T07:54:57Z<p>Tristan Miller: /* Software - Uncategorized and miscellaneous */ remove entries already categorized</p>
<hr />
<div><div class="usermessage"><br />
* Please ''do not add anything new to this list''; we would like to eventually eliminate this list.<br />
* Please help us by moving links into categories; add new categories to [[Tools and Software]] if needed.<br />
* Please add new items to the [[List of resources by language]] where appropriate.<br />
</div><br />
<br />
==[[Software]] - Uncategorized and miscellaneous==<br />
<br />
*[http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/bookcode/allen/0.html Code from James Allen's "Natural Language Understanding" (code at CMU)]<br />
*[http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/bookcode/nlp_pp/0.html Code from Michael Covington's "NLP for Prolog Programmers" (code at CMU)]<br />
*[http://www.dtreg.com/ DTREG decision tree generator]<br />
*[http://homepage.mac.com/bncweb/home.html BNCweb: A Web-Based Interface to the British National Corpus] <br />
*[http://nlg18.csie.ntu.edu.tw:8080/opinion/index.html Chinese sentiment dictionary NTUSD] <br />
*[http://www.athel.com/colloc.html Collocate] <br />
*[http://lingo.stanford.edu/ CSLI LinGO Lab (Stanford)] <br />
*[http://www.lsi.upc.es/~nlp/freeling/ FreeLing 1.1] <br />
*[http://www.webir.org/resources.html IR and IE on the web] <br />
*[http://www.comp.nus.edu.sg/~qiul/NLPTools/JavaRAP.html JavaRAP] <br />
*[https://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library)] <br />
*[http://www.linguastream.org LinguaStream]<br />
*[http://xlex.uni-muenster.de/ MTP Xlex/www] <br />
*[http://www.langsoft.ch Natural Language Processing software] <br />
*http://opennlp.sf.net OpenNLP]<br />
*[http://www.dcs.shef.ac.uk/~francois/personality/recognizer.html Personality Recognizer from Text]<br />
*[http://www.nzdl.org/ELKB/ Roget's Thesaurus as an Electronic Lexical Knowledge Base] <br />
*[http://www.chass.utoronto.ca/tact/ Text Analysis Computing Tools (TACT)] <br />
*[http://odur.let.rug.nl/~vannoord/TextCat/ TextCat] <br />
*[http://igm.univ-mlv.fr/~unitex/ Unitex] <br />
*[http://www.mith2.umd.edu/products/ver-mach/ Versioning Machine 2.0]<br />
<br />
==Applications==<br />
<!-- Please keep this list in alphabetical order --><br />
<br />
<br />
*[http://webdeptos.uma.es/filifa/personal/amoreno/indexer/ BNC Indexer]<br />
*[http://www.brainhat.com/ Brainhat Natural Language Processing]<br />
*[http://www.chilibot.net/ Chilibot: NLP based miner for gene/protein/keyword relationships]<br />
*[http://www.bultreebank.org/clark CLaRK System]<br />
*[http://delphesintl.com/ Delphes Technologies International]<br />
*[http://www.dtreg.com DTREG 2.0 decision trees with TreeBoost]<br />
*[http://www.dfki.de/lt/registry/apps/korek21.html KOREKTOR 2.0 (at the DFKI NLP archive)]<br />
*[http://www.xs4all.nl/~bsarempt/linguistics/index.html KURA 1.0]<br />
*[http://ngram.sourceforge.net Ngram Statistics Package], identify collocations<br />
*[http://www.ccs.neu.edu/home/futrelle/bionlp/commercial/opus.html Opus, a commercial biology text mining system]<br />
*[http://sourceforge.net/projects/pytalk/ Project: Pytalk]<br />
*[http://www.wagsoft.com/RSTTool/ Release of RSTTool: RSTTool 2.7]<br />
*[http://senseclusters.sourceforge.net SenseClusters], cluster similar contexts<br />
*[http://www.softissimo.com/ SOFTISSIMO]<br />
*[http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html TreeTagger]<br />
<br />
==Tools==<br />
<br />
*[http://www.ldc.upenn.edu/Projects/ACE/Tools/ Automatic Content Extraction (ACE): Annotation Tools]<br />
*[http://www.norvig.com/paip/grammar.lisp a simple grammar of English]<br />
*[http://sourceforge.net/projects/acopost/ ACOPOST]<br />
*[http://acdc.linguateca.pt/example_alignment.html Alignment of bilingual corpora performed with EasyAlign]<br />
*[http://www.lsi.upc.es/~lambert/software/AlignmentSet.html Alignment Set Toolkit]<br />
*[http://lucene.apache.org/java/docs/ Apache Lucene]<br />
*[http://www.arabeyes.org/ Arabeyes Project]<br />
*[http://misshoover.si.umich.edu/~zzheng/sentence/ Automatic English Sentence Segmentation]<br />
*[http://www.clg.wlv.ac.uk/projects/CAST/demos.php Automatic Summarization Demos]<br />
*[http://www.r.dl.itc.u-tokyo.ac.jp/~nakagawa/resource/termext/atr-e.html Automatic Term Extraction System]<br />
*[http://lael.pucsp.br/corpora/ Bancos de dados e Ferramentas de an`alise]<br />
*[http://www.ai.mit.edu/~murphyk/Software/BNT/bnt.html Bayes Net Toolbox for Matlab]<br />
*[http://bndev.sourceforge.net/ Bayesian Network tools in Java (BNJ)]<br />
*[http://sslmit.unibo.it/~baroni/bootcat.html BootCaT: Simple Utilities to Bootstrap Corpora and Terms from the Web]<br />
*[http://callisto.mitre.org/ Callisto Annotation Tool]<br />
*[http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T13 CCGBank]<br />
*[http://lael.pucsp.br/corpora/alinhador/ CEPRIL aligner]<br />
*[http://pie.usna.edu/explorec.html Chargrams Database from British National Corpus]<br />
*[http://www.bultreebank.org/clark/index.html CLaRK System]<br />
*[http://dlt4.mit.edu/~dr/COALS/ COALS: Correlated Occurrence Analogue to Lexical Semantics]<br />
*[ftp://cs.nyu.edu/pub/html/comlex.html/ Comlex]<br />
*[http://www.ai.mit.edu/projects/iiip/doc/cl-http/home-page.html Common Lisp Hypermedia Server]<br />
*[http://www.cpan.org/ Comprehensive Perl Archive Network]<br />
*[http://clg.wlv.ac.uk/projects/CAST/ Computer Aided Summarisation Tool (CAST)]<br />
*[http://infomap.stanford.edu/webdemo Concept Search Engine Information Mapping Demo (Center for the Study of Language and Information, Stanford University)]<br />
*[https://sourceforge.net/projects/concollate/ Concollate]<br />
*[http://borel.slu.edu/crubadan/ Corpus building for minority languages]<br />
*[http://montev.isi.edu:8000/align-tool/?CORPUS=de-news-morphix&AFILE=full-model1-50-50.gz Corpus De-News-Morphix Alignment Tool]<br />
*[http://search.cpan.org/dist/SuffixTree/ CPAN Suffix Tree Module]<br />
*[http://www.ucl.ac.uk/english-usage/diachronic/index.htm Creating a Parsed and Searchable Diachronic Corpus of Present-Day Spoken English]<br />
*[http://www.cis.upenn.edu/~dbikel/software.html#wn Dan Bikel's Java WordNet Library]<br />
*[http://www.dataharmony.com/ Data Harmony, Document Management Software]<br />
*[http://www.cs.ualberta.ca/~lindek/demos.htm Demos of dependency database, parser, and other tools]<br />
*[http://fuzzy.cs.uni-magdeburg.de/~borgelt/dtree.html Dtree - Decision and Regression Tree Induction]<br />
*[http://www.foreignword.com/dictionary/truespel/transpel.htm English-Truespel (USA Accent) Text Conversion Tool]<br />
*[http://www.cs.jhu.edu/~brill/ Eric Brill's Part of Speech Tagger]<br />
*[http://odur.let.rug.nl/~vannoord/Fsa/Manual/node1.html Finite State Automata Utilities v6]<br />
*[http://www.jaist.ac.jp/~hieuxuan/flexcrfs/flexcrfs.html FlexCRFs: Flexible Conditional Random Fields]<br />
*[http://garraf.epsevg.upc.es/freeling/ FreeLing 1.2]<br />
*[http://grid.let.rug.nl/~vannoord/Fsa/fsa.html FSA6.2xx: Finite State Automata Utilities]<br />
*[http://gate.ac.uk/ GATE (General Architecture for Text Engineering)]<br />
*[http://www.clsp.jhu.edu/ws2005/groups/statistical/GenPar.html GenPar Toolkit for Generalized Parsing]<br />
*[http://www.parc.xerox.com/istl/groups/nltt/medley/ Grammar Writer's Workbench for Lexical Functional Grammar]<br />
*[http://heartofgold.dfki.de Heart of Gold - XML-based middleware for the integration of (deep and shallow) NLP components]<br />
*[http://htk.eng.cam.ac.uk Hidden Markov Model Toolkit]<br />
*[http://www.ida.liu.se/~nlplab/ILink/ I*Link]<br />
*[http://www.kbsim.com/ifind.html iFind KBSim.com - Knowledge-Based Simulations, Inc.]<br />
*[http://www.infogistics.com/posdemo.htm Infogistics: NLProcessor Interactive Demo]<br />
*[http://www.isi.edu/~marcu/software.html ISI's version of the RSTTool]<br />
*[http://www-2.cs.cmu.edu/~javabayes/Home/ JavaBayes - v0.346]<br />
*[http://www.dcs.shef.ac.uk/~francois/jmrc/index.html jMRC - MRC Psycholinguistic Database Java Interface]<br />
*[http://www.comp.leeds.ac.uk/andyr/software/jTokeniser/ jTokeniser]<br />
*[http://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library)]<br />
*[http://www.ukp.tu-darmstadt.de/software/JWPL/ JWPL (Java Wikipedia Library)] <br />
*[http://sslmit.unibo.it/%7ebaroni/welcome_to_knorpora.html Knorpora 1.0]<br />
*[http://miniappolis.com/KWiCFinder/KWiCFinderHome.html KWiCFinder]<br />
*[http://www.kwicfinder.com/KWiCFinder.html Kwicfinder]<br />
*[http://odur.let.rug.nl/~vannoord/TextCat/competitors.html Language Identification Tools]<br />
*[http://www-2.cs.cmu.edu/~lemur/download.html Lemur Toolkit Download]<br />
*[http://www.lemurproject.org/ Lemur Toolkit Website]<br />
*[http://www.leximancer.com/ Leximancer]<br />
*[http://www.csie.ntu.edu.tw/~cjlin/libsvm/ LIBSVM: A Library for Support Vector Machines]<br />
*[http://search.cpan.org/~lgoddard/Lingua-Syllable-0.03/Syllable.pm Lingua-Syllable]<br />
*[http://listserv.linguistlist.org/cgi-bin/wa?A2=ind0109&L=corpora&P=R729 list of POS taggers]<br />
*[http://ucrel.lancs.ac.uk/llwizard.html Log-likelihood calculator]<br />
*[ftp://ftp.ncbi.nlm.nih.gov/pub/lsmith/MedPost/medpost.tar.gz MedPost: A Part-of-Speech Tagger for BioMedical text]<br />
*[http://www.lexically.net/wordsmith/version4/index.htm Mike Scott's Web - Wordsmith Tools]<br />
*[http://mmax.eml-research.de MMAX Annotation Tool]<br />
*[http://www.dcs.shef.ac.uk/research/ilash/Moby/ Moby Database]<br />
*[http://search.cpan.org/author/SHLOMOY/Lingua-EN-Sentence-0.25/lib/Lingua/EN/Sentence.pm Module for splitting text into sentences]<br />
*[http://www.cs.berkeley.edu/~aiken/moss.html Moss: A System for Detecting Software Plagiarism]<br />
*[http://www.natlantech.com/lingbench_ide.html Natlanco]<br />
*[http://www.cs.jhu.edu/~brill/code.html Natural Language Processing Systems]<br />
*[http://www.ltg.ed.ac.uk/NITE/ NITE XML Toolkit]<br />
*[http://nltk.sourceforge.net NLTK - Natural Language Toolkit]<br />
*[http://crl.nmsu.edu/Tools/Software/ NMSU Natural Language Processing Tools]<br />
*[http://annotation.semanticweb.org/ontomat/index.html Ontomat Homepage]<br />
*[http://teach-computers.org/word-expert.html Open Mind]<br />
*[http://davinci.cs.ucdavis.edu/ OpenRCT Home]<br />
*[http://www.oriel.org/homonym.htm ORIEL -- Online Research Information Environment for the Life Sciences]<br />
*[http://clg.wlv.ac.uk/projects/PALinkA/ PALinkA: A Resource Annotation Tool]<br />
*[http://www.sil.org/ PC-KIMMO, Englex, PC-PATR, and PC-PARSE]<br />
*[http://wall.jussieu.fr/dyn/Context2 perl concordancer]<br />
*[http://www.tartarus.org/~martin/PorterStemmer/index.html Porter Stemming Algorithm]<br />
*[http://www.sciences.univ-nantes.fr/info/perso/permanents/enguehard/recherche/CoRRecT/CoRRecT_gb.htm Project CoRRecT: Reference Corpus for the Recognition of Terms]<br />
*[http://protege.stanford.edu/ Protege Project]<br />
*[http://www.lingsoft.fi/cgi-pub/engcg Publically available POS tagger]<br />
*[http://corpus.leeds.ac.uk/query-zh.html Query to Chinese Corpora]<br />
*[http://www-rali.iro.umontreal.ca/Reacc/ R&eacute;acc - reaccenting software]<br />
*[http://rdues.uce.ac.uk/acronym.shtml RDUES ACRONYM (Automatic Collocational Retrieval of NYMs) Project]<br />
*[http://www.comp.nus.edu.sg/~rpnlpir/daemonCollins/ README for the daemonized version of Collins' Parser]<br />
*[http://www.research-lab.com/ Research-lab.com]<br />
*[http://www.reitter-it-media.de/compling/index.html RST LaTeX (Reitter IT and Media)]<br />
*[http://herzberg.ca.sandia.gov/jess/index.shtml Rule Engine for the Java Platform]<br />
*[http://elib.cs.berkeley.edu/src/satz/ SATZ--Adaptive Sentence Boundary Detector]<br />
*[http://ixa.si.ehu.es/Ixa/resources/selprefs Selectional Preferences Extracted from Semcor for WordNet 1.6 Synsets (v 1.0)]<br />
*[http://ilk.uvt.nl/~sabine/chunklink/ Software - The chunklink script, by Sabine Buchholz]<br />
*[http://people.csail.mit.edu/people/mcollins/code.html Software and Data Sets for Collins Natural Language Parser]<br />
*[http://senta.di.ubi.pt Software for the Extraction of N-ary Textual Associations (SENTA)]<br />
*[http://www-a2k.is.tokushima-u.ac.jp/member/kita/NLP/nlp_tools.html Software Tools for NLP]<br />
*[http://sprout.dfki.de SProUT - Shallow Processing with Unification and Typed Feature Structures]<br />
*[http://www-nlp.stanford.edu/software/lex-parser.shtml Stanford Parser]<br />
*[http://www.lsi.upc.edu/%7Enlp/SVMTool/ SVMTool]<br />
*[http://swesum.nada.kth.se/index-eng.html SweSum - Automatic Text Summarizer (with PRM)]<br />
*[http://www.wagsoft.com/Coder/ Systemic Coder -- a Text Markup Tool (Version 4.5)]<br />
*[http://www-2.cs.cmu.edu/~lenzo/t2p/ t2p: Text-to-Phoneme Converter Builder]<br />
*[http://www.d.umn.edu/~tpederse/parallel.html Ted Pedersen - Tools for Parallel Text]<br />
*[http://lsi.research.telcordia.com/ Telcordia Latent Semantic Indexing Demo Machine]<br />
*[http://www.tei-c.org/Software/index.html Text Encoding Initiative --Tools]<br />
*[http://www.comp.lancs.ac.uk/computing/research/ucrel/claws/tagservice.html The CLAWS tagging service]<br />
*[http://www.clsp.jhu.edu/ws99/projects/mt/toolkit/ The EGYPT Statistical Machine Translation Toolkit]<br />
*[http://www.ims.uni-stuttgart.de/CorpusToolbox/ The IMS Corpus Toolbox Webpage]<br />
*[http://jazzy.sourceforge.net/ The Java Open Source Spell Checker]<br />
*[http://www.findingnames.net/ The Naming Company]<br />
*[http://timex2.mitre.org/taggers/timex2_taggers.html TIMEX2 Taggers]<br />
*[http://www.coli.uni-sb.de/~thorsten/tnt/ TnT - Statistical Part-of-Speech Tagger]<br />
*[http://www.cs.columbia.edu/nlp/tools.html Tools developed at Columbia University (FUF, Surge, Crep, Segmenter, Verber, Xtract)]<br />
*[http://www.torch.ch Torch3]<br />
*[http://main.amu.edu.pl/~sipkadan/lingo.htm Turbo Lingo]<br />
*[http://stp.ling.uu.se/cgi-bin/joerg/Uplug Uplug]<br />
*[http://wordlist.sourceforge.net/varcon-readme VarCon (Variant Conversion Info)]<br />
*[http://www.edict.com.hk/concordance/ Virtual Language Centre's Web Concordancer]<br />
*[http://www.textanalysis.com/ VisualText]<br />
*[http://sourceforge.net/projects/wordfreak Wordfreak]<br />
*[http://www.d.umn.edu/~tpederse/wsdshell.html WSD Shell]<br />
*[http://www.xml-ces.org/ XCES: Corpus Encoding Standard for XML]<br />
<br />
== WordNet stuff (placeholder) ==<br />
<br />
* [http://search.cpan.org/dist/WordNet-SenseRelate Word-Net SenseRelate]<br />
* [http://search.cpan.org/dist/WordNet-Similarity Word-Net Similarity]<br />
* [http://www.clres.com/WordNet.html alphabetic version of WordNet 2.0]<br />
* [http://www.ai.mit.edu/~jrennie/WordNet/ Perl interface to WordNet]<br />
<br />
== QA systems (placeholder, needs to go somewhere else) ==<br />
<br />
* [http://www.answerbus.com/index.shtml Answerbus -- Automatic Language Detection Software ]<br />
* [http://demos.inf.ed.ac.uk:8080/qualim/ QuALiM Question Answering System - Searches Wikipedia]<br />
* [http://start.csail.mit.edu/ START Natural Language Question Answering System]<br />
* [http://www.umiacs.umd.edu/~jimmylin/downloads/index.html Aranea Question Answering System]<br />
* [http://webglimpse.net/ Webglimpse]<br />
* [http://www.openchannelsoftware.org/projects/Qanda Qanda: Open source question answering system]<br />
<br />
==Miscellaneous==<br />
<br />
* [http://homepage.mac.com/bncweb/home.html BNCweb: A Web-Based Interface to the British National Corpus ]<br />
* [http://lingo.stanford.edu/ CSLI LinGO Lab (Stanford) ]<br />
* [http://nlg18.csie.ntu.edu.tw:8080/opinion/index.html Chinese sentiment dictionary NTUSD ]<br />
* [http://www.athel.com/colloc.html Collocate ]<br />
* [http://www.lsi.upc.es/~nlp/freeling/ FreeLing 1.1 ]<br />
* [http://www.webir.org/resources.html IR and IE on the web ]<br />
* [https://sourceforge.net/projects/jwordnet/ JWNL (Java WordNet Library) ]<br />
* [http://www.comp.nus.edu.sg/~qiul/NLPTools/JavaRAP.html JavaRAP ]<br />
* [http://xlex.uni-muenster.de/ MTP Xlex/www ]<br />
* [http://www.langsoft.ch Natural Language Processing software ]<br />
* [http://www.dfki.de/lt/registry/draft.html Natural Language Software Registry (at DFKI) ]<br />
* [http://www.nzdl.org/ELKB/ Roget's Thesaurus as an Electronic Lexical Knowledge Base ]<br />
* [http://www.chass.utoronto.ca/tact/ Text Analysis Computing Tools (TACT) ]<br />
* [http://odur.let.rug.nl/~vannoord/TextCat/ TextCat ]<br />
* [http://igm.univ-mlv.fr/~unitex/ Unitex ]<br />
<br />
==See also==<br />
<br />
* [[Named entity recognizers]]<br />
<br />
[[Category:Software]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Resources_for_Esperanto&diff=10346Resources for Esperanto2013-10-14T15:50:24Z<p>Tristan Miller: == Software ==;[http://www.nothingisreal.com/eoconv/ eoconv]:Converts text files to and from various Esperanto text encodings</p>
<hr />
<div>== Software ==<br />
;[http://www.nothingisreal.com/eoconv/ eoconv]<br />
:Converts text files to and from various Esperanto text encodings<br />
<br />
[[Category:Resources by language|English]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=List_of_resources_by_language&diff=10345List of resources by language2013-10-14T15:47:57Z<p>Tristan Miller: /* E */ Resources for Esperanto</p>
<hr />
<div>List of pages which give links and commentary on computational resources by language.<br />
<br />
Quick links:<br />
<br />
* [[Resources for English]]<br />
* [[Multilingual resources|Resources for Multilingual Applications]]<br />
<br />
See also:<br />
<br />
* [http://www.ethnologue.com/ Ethnologue: Languages of the World]<br />
* [[Language Identification Tools]]<br />
<br />
<br />
==A==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Albanian]]<br />
* [[Resources for Amharic]]<br />
* [[Resources for Arabic]]<br />
* [[Resources for Afrikaans]]<br />
<br />
==B==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Basque]]<br />
* [[Resources for Bulgarian]]<br />
* [[Resources for Breton]]<br />
<br />
==C==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Catalan]]<br />
* [[Resources for Chinese]]<br />
* [[Resources for Croatian]] (see also [[Resources for Serbian]], [[Resources for Bosnian]], [[Resources for Serbo-Croatian]])<br />
* [[Resources for Czech]]<br />
<br />
==D==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Danish]]<br />
* [[Resources for Dutch]]<br />
<br />
==E==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for English]]<br />
* [[Resources for Esperanto]]<br />
* [[Resources for Estonian]]<br />
<br />
==F==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Faroese]]<br />
* [[Resources for Finnish]]<br />
* [[Resources for French]]<br />
<br />
==G==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Galician]]<br />
* [[Resources for Georgian]]<br />
* [[Resources for German]]<br />
* [[Resources for Greek]]<br />
* [[Resources for Greenlandic]]<br />
<br />
==H==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Haitian]]<br />
* [[Resources for Hebrew]]<br />
* [[Resources for Hindi]]<br />
* [[Resources for Hungarian]]<br />
<br />
==I==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Icelandic]]<br />
* [[Resources for Indonesian]]<br />
* [[Resources for Inuktitut]]<br />
* [[Resources for Iñupiaq]]<br />
* [[Resources for Iranian]]<br />
* [[Resources for Italian]]<br />
* [[Resources for Irish]]<br />
<br />
==J==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Japanese]]<br />
<br />
==K==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Kannada]]<br />
* [[Resources for Korean]]<br />
* [[Resources for Komi]]<br />
* [[Resources for Kurdish]]<br />
<br />
==L==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Lithuanian]]<br />
<br />
==M==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Macedonian]]<br />
* [[Resources for Malay]]<br />
* [[Resources for Maltese]]<br />
* [[Resources for Montenegrin]]<br />
* [[Multilingual resources|Resources for Multilingual Applications]]<br />
<br />
==N==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Norwegian]]<br />
* [[Resources for Navajo]]<br />
<br />
==O==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Occitan]]<br />
<br />
==P==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Pashto]]<br />
* [[Resources for Persian]]<br />
* [[Resources for Polish]]<br />
* [[Resources for Portugese]]<br />
* [[Resources for Punjabi]]<br />
<br />
==Q==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Quechua]]<br />
<br />
==R==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Romanian]]<br />
* [[Resources for Russian]]<br />
<br />
==S==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Sámi]]<br />
* [[Resources for Sanskrit]]<br />
* [[Resources for Slovak]]<br />
* [[Resources for Slovenian]]<br />
* [[Resources for Sorbian]]<br />
* [[Resources for Spanish]]<br />
* [[Resources for Swahili]]<br />
* [[Resources for Swedish]]<br />
<br />
==T==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Tajik]]<br />
* [[Resources for Turkish]]<br />
* [[Resources for Tigrinya]]<br />
* [[Resources for Telugu]]<br />
<br />
==U==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Ukrainian]]<br />
* [[Resources for Urdu]]<br />
<br />
==V==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Vietnamese]]<br />
<br />
==W==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Welsh]]<br />
<br />
==Z==<br />
__NOTOC__<br />
{{compactTOC2}}<br />
* [[Resources for Zulu]]<br />
<br />
==See also==<br />
<br />
* [[Resources for African languages]]<br />
<br />
[[Category:Resources by language|*]]</div>Tristan Millerhttps://aclweb.org/aclwiki/index.php?title=Multilingual_Tools_and_Software&diff=10344Multilingual Tools and Software2013-10-14T15:47:10Z<p>Tristan Miller: Remove dead/uniligual links; add several more tools; update links; reformat and sort list</p>
<hr />
<div>For individual languages, see [[List of resources by language]].<br />
<br />
<br />
<!-- Please keep this list in alphabetical order --><br />
;[https://code.google.com/p/csniper/ CSniper]<br />
:A search-based annotation tool to help distributed annotation teams finding infrequent linguistic phenomena in large corpora<br />
;[http://fmg-www.cs.ucla.edu/geoff/ispell-dictionaries.html Dictionaries for International Ispell]<br />
:Dictionaries and affix files for various languages<br />
;[https://code.google.com/p/dkpro-core-asl/ DKPro Core]<br />
:A collection of software components for NLP based on the Apache UIMA framework<br />
;[https://code.google.com/p/dkpro-lab/ DKPro Lab]<br />
:A lightweight framework for parameter sweeping experiments<br />
;[https://code.google.com/p/dkpro-lsr/ DKPro LSR]<br />
:A unified API for several lexical-semantic resources, including GermaNet, OpenThesaurus, Wikipedia, Wiktionary, and WordNet<br />
;[https://code.google.com/p/dkpro-similarity-asl/ DKPro Similarity]<br />
:An open source software package for developing text similarity algorithms<br />
;[https://code.google.com/p/dkpro-spelling-asl/ DKPro Spelling]<br />
:A collection of software components for spelling correction, especially for correcting real-word spelling errors<br />
;[https://code.google.com/p/dkpro-statistics/ DKPro Statistics]<br />
:A collection of statistical tools, currently including correlation and inter-rater agreement methods<br />
;[https://code.google.com/p/dkpro-tc/ DKPro Text Classification]<br />
:A UIMA-based text classification framework<br />
;[https://code.google.com/p/dkpro-wsd/ DKPro WSD]<br />
:A modular, extensible Java framework for word sense disambiguation<br />
;[http://heartofgold.dfki.de Heart of Gold]<br />
:XML-based middleware for the integration of (deep and shallow) NLP components<br />
;[http://www.ukp.tu-darmstadt.de/software/jobimtext/ JoBimText]<br />
:A software solution for automatic text expansion using contextualized distributional similarity<br />
;[https://code.google.com/p/jowkl/ JOWKL]<br />
:A Java-based API for OmegaWiki<br />
;[https://code.google.com/p/jwktl/ JWKTL]<br />
:A Java API for the free multilingual online dictionary Wiktionary<br />
;[https://code.google.com/p/jwpl/ JWPL]<br />
:A Java API for Wikipedia<br />
;[http://nlp.stanford.edu/kirrkirr/ Kirrkirr 4.0 Dictionary Program]<br />
:Software for the exploration of indigenous language dictionaries<br />
;[https://sites.google.com/site/morfetteweb/ Morfette]<br />
:A tool for supervised learning of inflectional morphology<br />
;[http://www.lpl.univ-aix.fr/projects/multext/MtRecode/ MtRecode]<br />
:Character conversion program<br />
;[http://www.lpl.univ-aix.fr/projects/multext/MtScript/ MtScript]<br />
:The Multext multi-lingual text editor<br />
;[http://www.computing.dcu.ie/~ygraham/software.html RIA Open Source Rule Induction Tool]<br />
:A tool for automatic induction of transfer rules for Transfer-Based Statistical Machine Translation using dependency structures ([[LFG]] f-structures)<br />
;[http://sprout.dfki.de SProUT]<br />
:Shallow Processing with Unification and Typed Feature Structures<br />
;[http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/ TIGERSearch]<br />
:Tools for linguistic text exploration<br />
;[https://code.google.com/p/uby/ UBY]<br />
:A network of lexical resources interlinked at the sense level and a project on semantic integration of lexical resources for NLP applications<br />
;[https://code.google.com/p/webanno/ WebAnno]<br />
:A general purpose web-based annotation tool for a wide range of linguistic annotations.<br />
;[http://beta.visl.sdu.dk/cg3.html vislcg3]<br />
:A tool that parses [[Constraint Grammar]] rules, commonly used for rule-based morphological disambiguation, syntactic function labelling and dependency annotation<br />
<!-- Please keep this list in alphabetical order --><br />
<br />
See also [[Multilingual resources]].<br />
<br />
<br />
[[Category:Resources by language|Multilingual]]</div>Tristan Miller