Difference between revisions of "Employment opportunities, postdoctoral positions, summer jobs"

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* See also the [http://linguistlist.org/jobs Linguist Job List].
 
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== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==
  
−
==Internship position available in Natural Language Processing at Adobe Research==
+
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain
−
* Employer: Adobe Systems Incorporated
+
* Title: PhD Scholarship
−
* Title: NLP Scientist Intern
+
* Specialty: Text Mining, Information Extraction, Music Information Retrieval
−
* Natural Language Processing, Machine Learning, Dialog Systems.
+
* Location: Barcelona, Spain
−
* Location: San Jose, CA
+
* Deadline: Until candidate is found
−
* Deadline: open until the position is filled
+
* Date posted: June 10, 2017
−
* Date Posted: February 24, 2015
+
* Contact: [mailto:horacio.saggion@upf.edu]
−
* Trung Bui: bui@adobe.com
 
  
−
'''Description''':
 
−
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.
 
  
−
'''Key Qualifications'''
+
PhD position on data-driven methodologies for music knowledge extraction
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*Experience with semantic parsing, dialog systems.
+
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.
−
*Experience with machine learning, deep learning.
+
−
*Good programming skills in Java and/or Python
+
Supervisors of the position: Xavier Serra and Horacio Saggion
 +
Contact for application:  Aurelio Ruiz (aurelio.ruiz@upf.edu)
 +
 +
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.
 +
 +
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 .
  
−
'''Education'''
 
−
M.S. or PhD student in Computer Science or related field
 
  
−
'''Additional Requirements'''
 
−
No.
 
  
−
== Postdoc in Advanced Machine Learning (with an Emphasis on NLP) ==
+
== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
−
*Employer: University of Notre Dame
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
−
*Job Number: 4015639
+
* Title: Scientific System Developer
−
*Date Posted: 02/17/2015
+
* Specialty: Argument Mining, Machine Learning, Big Data Analysis
−
*Application Deadline: Open Until Filled
+
* Location: Darmstadt
−
*Online application: http://www.postdocjobs.com/jobs/jobdetail.php?jobid=4015639
+
* Deadline: May 31, 2017
 +
* Date posted: May 3, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
  
−
'''Job Description'''
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a
  
−
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.
+
'''Scientific System Developer'''<br>
 +
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
−
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.
+
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.  
  
−
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.
+
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.
  
−
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.
+
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.
 +
 
 +
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).
 +
 
 +
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.
 +
 
 +
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297
 +
We look forward to receiving your application!
 +
 
 +
 
 +
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
 +
 
 +
* Employer: Cardiff University
 +
* Title: Postdoctoral Research Associate
 +
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI
 +
* Location: Cardiff, UK
 +
* Deadline: May 20, 2017
 +
* Date posted: April 20, 2017
 +
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]
 +
 
 +
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:
 +
* 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.
 +
*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.
 +
 
 +
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)
 +
 
 +
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.
 +
 
 +
 
 +
'''More information'''
 +
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.
 +
 
 +
 
 +
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
 +
 
 +
* Employer: University of Colorado Boulder
 +
* Title: Postdoctoral Research Associate
 +
* Specialty: Advanced Machine Learning
 +
* Location: Boulder, Colorado, United States
 +
* Deadline: Ongoing, desired start Summer/Fall 2017
 +
* Date posted: March 31, 2017
 +
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
 +
 
 +
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
 +
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
 +
 
 +
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.
 +
 
 +
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).
 +
 
 +
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.
 +
 
 +
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.
  
 
'''Required'''
 
'''Required'''
 +
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)
 +
* 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)
 +
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record
 +
 +
'''Desired'''
 +
* 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)
 +
* Experience mentoring graduate and undergraduate students
  
−
(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
+
'''Job Details'''
 +
* 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.
 +
* Start date is negotiable, but anticipated for Summer/Fall 2017.
 +
* 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.
  
−
'''Desired'''
+
'''How to apply''' <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.
  
−
(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
+
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.
  
−
For more information see the application link above.
+
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].
  
−
== Software Engineer/NLG Specialist in Sydney, Aus - Natural Lanaguage Generation==
+
'''Questions''' <br/>
−
*Employer: Macquarie Group
+
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
−
*Title: Software Engineer/NLG Specialist
 
−
*Specialties: Natural Language Generation, Application Development, Linguistics
 
−
*Location: Sydney, Australia
 
−
*Date posted: 29 January 2015
 
−
*Contact information: andy.logan@macquarie.com
 
−
*Online application: http://www.careers.macquarie.com/cw/en/job/923649/software-engineers-nlpnlg-programming-equities-research
 
  
−
'''Job Description'''
 
−
*Unique opportunity within the Equities Research space for a Engineer with strong NLG experience
 
−
*New Systems Implementation with Opportunity to push the envelope within Research
 
−
*Permanent Opportunity – Sydney CBD Location
 
  
−
'''About the role'''
+
== Researcher in Machine Learning and NLP, DFKI, Germany ==
  
−
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.  
+
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany
 +
* Title: Researcher
 +
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
 +
* Location: Saarbruecken
 +
* Deadline: March 31, 2017
 +
* Date posted: March 13, 2017
 +
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]
  
−
'''Key Responsibilities'''
+
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.
−
*Design and Develop our first NLG/NLP Application within Equities Research
 
−
*Work closely with the vendor to understand the application limitations and functionality
 
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*Drive the development with the Head of Research as well as industry analysts
 
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*Mature the offering and look for further areas of development within the business
 
  
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'''About You'''
+
'''Key research responsibilities''' include:
 +
* machine and deep learning for natural language processing/machine translation
 +
* software development and integration
 +
* publication in top-tier conferences and journals
  
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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:
+
'''General responsibilities''' include:
 +
* engagement with industry partners and contract research
 +
* identification of funding opportunities and engagement in proposal writing
 +
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations
 +
* administrative work associated with programmes of research
  
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*Tenacity to produce different If Statements and to develop the platform further
+
'''Requirements:'''
−
*Strong interest in Artificial Intelligence/Machine Based Learning.
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* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar
−
*Keen interest in finance
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* Strong background and track record in machine learning, neural nets and deep learning
−
*Self Starter and strong attention to detail to really drive uptake of the platform
+
* Strong background and track record in NLP and MT - Excellent programming skills
 +
* Excellent problem solving skills, independent and creative thinking
 +
* Excellent team working and communication skills
 +
* Excellent command of written and oral English
 +
* Command of German and other  languages not a requirement but helpful
  
−
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'''
+
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).
  
−
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'''
+
'''Working environment:'''
 +
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.
  
−
== PostDoc Position in Heidelberg (NLP, Networks, Databases, Machine Learning)==
+
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.
−
*Employer: Heidelberg Institute for Theoretical Studies gGmbH (HITS)
 
−
*Title: PostDoc
 
−
*Specialties: Natural Language Processing, Networks, Databases, Machine Learning
 
−
*Location: Heidelberg, Germany
 
−
*Deadline: 20 February 2015
 
−
*Date posted: 29 January 2015
 
−
*Contact information: michael.strube (at) h-its.org
 
−
*Online application: https://application.h-its.org/intern/register.php?id=o51kdq1
 
  
−
'''Job Description'''
+
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.
−
PostDoc position available in the NLP group at the Heidelberg Institute for Theoretical Studies (HITS) in Heidelberg, Germany
 
  
−
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.
+
'''Geographical environment:'''
 +
[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.
  
−
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.
+
'''Starting date, duration, salary:'''
 +
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.
  
−
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.
+
'''Application:'''
 +
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.
  
−
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.
 
  
−
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)
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
  
−
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).
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
 +
* Title: Associate Research Scientist
 +
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
 +
* Location: Darmstadt
 +
* Deadline: March 8, 2017
 +
* Date posted: February 21, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]
  
 +
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
  
−
==Postdoc position in Cardiff (NLP, IR, machine learning)==
+
'''Associate Research Scientist'''<br />
−
*Employer: Cardiff University
+
'''(PostDoc- or PhD-level; for an initial term of two years)'''
−
*Title: Postdoc
 
−
*Specialties: Natural language processing, information retrieval, machine learning, distributional models, relation extraction, commonsense resoning
 
−
*Location: Cardiff, UK
 
−
*Deadline: 3 February 2015
 
−
*Date posted: 9 January 2015
 
−
*Contact information: SchockaertS1@cardiff.ac.uk
 
  
−
'''Job Description'''
+
to strengthen the group’s profile in the areas of Interactive Machine
 +
Learning (IML) or Natural Language Processing for Language Learning.
 +
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 Natural Language Processing
 +
for Language Learning are the focus areas researched in collaboration
 +
with partners in research and industry.
  
−
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.  
+
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.
  
−
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.
+
* 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.  
 +
* 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.  
  
−
'''Essential criteria'''
+
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
 +
large-scale data analysis, large-scale knowledge bases, and strong
 +
programming skills incl. Java. Experience with neural network
 +
architectures and a sense for user experience design are a strong
 +
plus. Combining fundamental NLP research on Interactive Machine
 +
Learning or Natural Language Processing with practical applications
 +
in different domains including education will be highly encouraged.
  
−
*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.
+
UKP’s wide cooperation network both within its own research community
−
*Excellent programming skills (java or C/C++).  
+
and with partners from research and industry provides an excellent
−
*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).
+
environment for the position to be filled. The Department of Computer
−
*Proven ability to communicate specialist ideas clearly in English using written media.  
+
Science of TU Darmstadt is regularly ranked among the top ones in  
−
*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.
+
respective rankings of German universities. Its unique research
−
*A PhD in Computer Science or closely related area, or equivalent experience.
+
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.
  
−
'''Desirable criteria'''
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
−
*Knowledge of statistical natural language processing.  
+
Applications from women are particularly encouraged. All other things
−
*Knowledge of unsupervised and semi-supervised learning.  
+
being equal, candidates with disabilities will be given preference.
−
*Knowledge of relation extraction.  
+
Please send the applications to:
−
*Experience with analysing large text corpora using a high-performance computing environment.  
+
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions
−
*Experience with dimensionality reduction methods such as multi-dimensional scaling, singular-value decomposition, and non-negative matrix factorisation.
+
are open until filled. Later applications may be considered if the
 +
position is still open.
  
−
'''More information'''
+
==  Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==
−
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.
+
*Employer: Northwestern University, USA
 +
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University
 +
*Speciality: Open area
 +
*Location: Evanston, IL, USA
 +
*Deadline: April 1, 2017
 +
*Date posted: February 17, 2017
 +
*Contact: matt-goldrick@northwestern.edu
  
−
==Post‐Doctoral and all levels of Research Scientist at the Allen Institute for Artificial Intelligence==
+
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).
−
*Employer: Allen Institute for Artificial Intelligence (AI2)
+
−
*Title: Post-doc/Research Scientist
+
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.
−
*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
+
−
*Location: Seattle, WA
+
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.
−
*Deadline: N/A, we are hiring throughout 2015
+
−
*Date posted: 12/9/2014
+
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.
−
*Contact information: ai2-info@allenai.org, allenai.org
 
  
−
'''Job Description'''
+
==  Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==
 +
*Employer: Cardiff University, UK
 +
*Title: Research Associate in Artificial Intelligence / Machine Learning
 +
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models
 +
*Location: Cardiff, UK
 +
*Deadline: March 2, 2017
 +
*Date posted: February 13, 2017
 +
*Contact: schockaerts1@cardiff.ac.uk
  
−
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.  
+
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.  
  
−
'''Position Summary'''
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
  
−
AI2 currently has projects in the following areas:
+
'''Essential criteria'''
−
*Language and Vision
 
−
*Information extraction and semantic parsing
 
−
*Question answering
 
−
*Language and reasoning
 
−
*Machine learning and theory formation
 
−
*Semantic search
 
−
*Diagram understanding
 
  
−
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.
+
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
 +
* 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.
 +
* A strong background in statistics and linear algebra.
 +
* Excellent programming skills.
 +
* Knowledge of current status of research in specialist field.
 +
* 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).
 +
* Ability to understand and apply for competitive research funding.
 +
* Proven ability in effective and persuasive communication.
 +
* Ability to supervise the work of others to focus team efforts and motivate individuals.
 +
* Proven ability to demonstrate creativity, innovation and team-working within work.
  
−
'''Applicant'''
+
'''Background about the university'''
  
−
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.
+
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.  
  
−
'''Application Process'''
+
'''Background about the project'''
  
−
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.
+
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.  
  
−
==Internship and Full-time positions available in Natural Language Processing at Apple Inc. (Siri)==
+
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.
−
* Employer: Apple Inc.
 
−
* Title: Language Understanding / Dialog Scientist
 
−
* Natural Language Processing, Machine Learning, Semantic Parsing, Dialog Systems.
 
−
* Location: Cupertino, CA
 
−
* Deadline: rolling
 
−
* Date Posted: December 2, 2014
 
−
* Thomas Kollar: tkollar@apple.com
 
  
−
'''Description''':
+
'''More information'''
−
Play a part in the next revolution in human-computer interaction. Contribute to a product that is redefining mobile computing. Create groundbreaking technology for large scale systems, spoken language understanding, big data, and artificial intelligence.  And work with the people who created the intelligent assistant that helps millions of people get things done — just by asking. Join the language understanding and dialog team at Apple. The Siri team is looking for exceptionally skilled and creative scientists and engineers eager to get involved in hands-on work improving the Siri experience.
 
  
−
'''Key Qualifications'''
+
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.
−
*Experience with semantic parsing, dialog modeling, information extraction, question answering, semantic web, syntactic parsing, machine translation, language modeling, sentiment analysis or speech processing.
 
−
*Experience with supervised, weakly-supervised and unsupervised machine learning algorithms.
 
−
*Exceptional analytical, troubleshooting and problem solving skills
 
−
*Ability to implement algorithms in Java and C++ in addition to performing experiments using scripting languages (Python, Perl, Ruby, bash).
 
−
*Strong software engineering skills
 
−
*Experience working with multilingual datasets
 
−
*Large scale data analysis experience using distributed clusters (e.g. Pig, Spark, GraphLab, GraphX, MapReduce) a plus
 
  
−
'''Description'''
+
==  Research Associates in Natural Language Processing / Text Mining,  University of Manchester, UK ==
−
You will be a part of a team that's responsible for a wide variety of natural language processing and spoken dialog systems research and development activities, including semantic parsing, dialog modeling, information extraction and question answering. Traditionally these conversational understanding applications have been focused on developing algorithms for a particular domain or language. Here at Siri, you will use large amounts of training data from Siri requests and the web to solve these problems across languages and domains. You are passionate about using your skills to implement and improve algorithms in order to create the phenomenal products. Because you'll be working closely with engineers from a number of other teams at Apple, you’ll need to be a team player who thrives in a fast paced environment.
+
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
 +
*Title: Research Associates in Natural Language Processing / Text Mining
 +
*Speciality: Natural Language Processing, Text Mining
 +
*Location: Manchester, UK
 +
*Deadline: March 13, 2017
 +
*Date posted: February 10, 2017
 +
*Contact: sophia.ananiadou@manchester.ac.uk
  
−
'''Education'''
+
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.
−
M.S. or PhD in Computer Science or related field
 
  
−
'''Additional Requirements'''
+
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.
−
2+ years of experience in natural language processing, speech processing, machine learning, artificial intelligence or dialog systems is desired.
 
  
−
==Multiple Tenure-Track Positions (w/focus in Data Analytics) at The Ohio State University Department of Computer Science and Engineering==
+
'''Skills'''
−
* Employer: The Ohio State University
 
−
* Title: Assistant/Associate/Full Professor
 
−
* Specialty: open, two positions in Data Analytics
 
−
* Location: Columbus, OH, USA
 
−
* Deadline: January 31, 2015 (Consideration starts November 2014)
 
−
* Date Posted: November 17, 2014
 
−
* Website: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi
 
  
−
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.
+
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.  
  
−
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.
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
−
The department is committed to enhancing faculty diversity; women, minorities, and individuals with disabilities are especially encouraged to apply.
+
'''Research Team'''
  
−
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.
+
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”.
  
−
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.
+
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).  
  
−
Review of applications will begin in November 2014 and will continue until the positions are filled.
+
Deadline of applications: 13/03/2017
  
−
The Ohio State University is an Equal Opportunity/Affirmative Action Employer.
+
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975

Revision as of 04:54, 10 June 2017

Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain

  • Employer: Universitat Pompeu Fabra [1], Barcelona, Spain
  • Title: PhD Scholarship
  • Specialty: Text Mining, Information Extraction, Music Information Retrieval
  • Location: Barcelona, Spain
  • Deadline: Until candidate is found
  • Date posted: June 10, 2017
  • Contact: [2]


PhD position on data-driven methodologies for music knowledge extraction 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.

Supervisors of the position: Xavier Serra and Horacio Saggion Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)

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.

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 .


Scientific System Developer, UKP Lab, TU Darmstadt

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a

Scientific System Developer
(PostDoc- or PhD-level; time-limited project position until April 2020)

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.

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.

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.

Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: 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.

Questions about the position can be directed to: Johannes Daxenberger; phone: [+49] (0)6151 16-25297 We look forward to receiving your application!


Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University

  • Employer: Cardiff University
  • Title: Postdoctoral Research Associate
  • Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI
  • Location: Cardiff, UK
  • Deadline: May 20, 2017
  • Date posted: April 20, 2017
  • Contact: Steven Schockaert

Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:

  • 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.
  • 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.

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)

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.


More information 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.


Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder

  • Employer: University of Colorado Boulder
  • Title: Postdoctoral Research Associate
  • Specialty: Advanced Machine Learning
  • Location: Boulder, Colorado, United States
  • Deadline: Ongoing, desired start Summer/Fall 2017
  • Date posted: March 31, 2017
  • Contact: Dr. Sidney D’Mello

Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)

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.

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).

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.

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.

Required

  • Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)
  • 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)
  • Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record

Desired

  • 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)
  • Experience mentoring graduate and undergraduate students

Job Details

  • 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.
  • Start date is negotiable, but anticipated for Summer/Fall 2017.
  • 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.

How to apply
Please complete Faculty/University Staff EEO Data (application) form (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.

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.

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 adacoordinator@colorado.edu.

Questions
Please email Dr. Sidney D’Mello


Researcher in Machine Learning and NLP, DFKI, Germany

  • Employer: DFKI GmbH, Germany
  • Title: Researcher
  • Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
  • Location: Saarbruecken
  • Deadline: March 31, 2017
  • Date posted: March 13, 2017
  • Contact: Prof. Josef van Genabith

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.

Key research responsibilities include:

  • machine and deep learning for natural language processing/machine translation
  • software development and integration
  • publication in top-tier conferences and journals

General responsibilities include:

  • engagement with industry partners and contract research
  • identification of funding opportunities and engagement in proposal writing
  • contribution to teaching and supervision in accordance with University and DFKI rules and regulations
  • administrative work associated with programmes of research

Requirements:

  • MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar
  • Strong background and track record in machine learning, neural nets and deep learning
  • Strong background and track record in NLP and MT - Excellent programming skills
  • Excellent problem solving skills, independent and creative thinking
  • Excellent team working and communication skills
  • Excellent command of written and oral English
  • Command of German and other languages not a requirement but helpful

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).

Working environment: 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.

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 QT21 on MT, the EU CEF funded ELRC project and the EU funded TRADR project on human-robot collaboration in disaster response scenarios.

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 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.

Geographical environment: 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.

Starting date, duration, salary: 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.

Application: 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 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 Prof. van Genabith for informal inquiries.


Associate Research Scientist, UKP Lab, TU Darmstadt

  • Employer: UKP Lab, Technische Universität Darmstadt, Germany
  • Title: Associate Research Scientist
  • Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
  • Location: Darmstadt
  • Deadline: March 8, 2017
  • Date posted: February 21, 2017
  • Contact: Prof. Iryna Gurevych

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings 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 Interactive Machine Learning (IML) or Natural Language Processing for Language Learning. 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 Natural Language Processing for Language Learning are the focus areas researched in collaboration with partners in research and industry.

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.

  • 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.
  • 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.

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 large-scale data analysis, large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures and a sense for user experience design are a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Natural Language Processing with practical applications in different domains including education will be highly encouraged.

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 "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.

Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the applications to: jobs@ukp.informatik.tu-darmstadt.de by 08.03.2017. The positions are open until filled. Later applications may be considered if the position is still open.

Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University

  • Employer: Northwestern University, USA
  • Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University
  • Speciality: Open area
  • Location: Evanston, IL, USA
  • Deadline: April 1, 2017
  • Date posted: February 17, 2017
  • Contact: matt-goldrick@northwestern.edu

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).

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.

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.

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.

Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK

  • Employer: Cardiff University, UK
  • Title: Research Associate in Artificial Intelligence / Machine Learning
  • Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models
  • Location: Cardiff, UK
  • Deadline: March 2, 2017
  • Date posted: February 13, 2017
  • Contact: schockaerts1@cardiff.ac.uk

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.

This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)

Essential criteria

  • Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
  • 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.
  • A strong background in statistics and linear algebra.
  • Excellent programming skills.
  • Knowledge of current status of research in specialist field.
  • 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).
  • Ability to understand and apply for competitive research funding.
  • Proven ability in effective and persuasive communication.
  • Ability to supervise the work of others to focus team efforts and motivate individuals.
  • Proven ability to demonstrate creativity, innovation and team-working within work.

Background about the university

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.

Background about the project

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.

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.

More information

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.

Research Associates in Natural Language Processing / Text Mining, University of Manchester, UK

  • Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
  • Title: Research Associates in Natural Language Processing / Text Mining
  • Speciality: Natural Language Processing, Text Mining
  • Location: Manchester, UK
  • Deadline: March 13, 2017
  • Date posted: February 10, 2017
  • Contact: sophia.ananiadou@manchester.ac.uk

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.

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.

Skills

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.

  • Duration of post: Immediately until 31st October 2018
  • Salary: £31,076-£38,183 per annum

Research Team

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”.

Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).

Deadline of applications: 13/03/2017

Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975

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