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

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* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* Archived postings:
 
* Archived postings:
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** [[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]]
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** [[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]]
 
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== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==
  
 +
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], 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: [mailto:horacio.saggion@upf.edu]
  
−
==Postdoc Positions at Johns Hopkins University==
 
  
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* Employer: Johns Hopkins University
+
PhD position on data-driven methodologies for music knowledge extraction
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* Title: Postdoc
+
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.
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* Specialty: NLP, Machine Learning, Social media analysis for computational social science, health/medicine
+
−
* Location: Baltimore, MD
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Supervisors of the position: Xavier Serra and Horacio Saggion
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* Deadline: March 31, 2016
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Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)
−
* Date posted: March 1, 2016
+
−
* Contact: [http://www.clsp.jhu.edu/employment-opportunities/ http://www.clsp.jhu.edu/employment-opportunities/]
+
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 .
  
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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.
 
  
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The center has a number of postdoctoral positions available for the coming year. Possible research topics include:
 
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* Trend Detection in Social Media
 
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* Broadly Multilingual Learning of Morphology
 
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* Stochastic approximation algorithms for subspace and multi-view representation learning
 
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* Analysis of large-scale time series data in healthcare
 
  
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Host faculty include:
+
== Scientific System Developer, UKP Lab, TU Darmstadt ==
−
Mark Dredze, David Yarowsky, Jason Eisner, Sanjeev Khudanpur, Benjamin Van Durme, Raman Arora, Suchi Saria
 
  
 +
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
 +
* Title: Scientific System Developer
 +
* Specialty: Argument Mining, Machine Learning, Big Data Analysis
 +
* Location: Darmstadt
 +
* Deadline: May 31, 2017
 +
* Date posted: May 3, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
  
−
==Associate/Full Professor in Computational Linguistics at Stony Brook University==
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a
−
* Employer: Department of Linguistics, Stony Brook University
 
−
* Title: Associate/Full Professor
 
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* Specialty: Computational Linguistics
 
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* Location: New York, USA
 
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* Deadline: March 14, 2016
 
−
* Date posted: February 17, 2015
 
−
* LinguistList Announcement: [http://linguistlist.org/issues/27/27-861.html http://linguistlist.org/issues/27/27-861.html]
 
−
* Contact: Lori Repetti [mailto:lori.repetti@stonybrook.edu lori.repetti@stonybrook.edu]
 
  
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'''Job Description'''
+
'''Scientific System Developer'''<br>
 +
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
−
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.
+
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 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.
+
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.
  
−
They will also be expected to
+
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.
  
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* Contribute to the ongoing development of the Department's degree programs in linguistics and computational linguistics,
+
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).  
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* 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,
 
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* Strengthen the department's connections with the local IT industry.
 
  
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Salary will be commensurate with education and experience.
+
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.
  
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'''Application'''
+
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!
  
−
Applications must be submitted via AcademicJobsOnline: [https://academicjobsonline.org/ajo/jobs/6983 https://academicjobsonline.org/ajo/jobs/6983]
 
  
−
==Research Scientist at the Allen Institute for Artificial Intelligence==
+
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
  
−
* Employer: Allen Institute for Artificial Intelligence (AI2)
+
* Employer: Cardiff University
−
* Title: Research Scientist
+
* Title: Postdoctoral Research Associate
−
* 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
+
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI
−
* Location: Seattle, WA
+
* Location: Cardiff, UK
−
* Deadline: N/A, we are hiring throughout 2016
+
* Deadline: May 20, 2017
−
* Date posted: 02/09/2016
+
* Date posted: April 20, 2017
−
* Contact information: ai2-info@allenai.org
+
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]
−
* Website: http://allenai.org/jobs.html
 
  
−
'''Job Description'''
+
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 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.  
+
*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.  
  
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'''Position Summary'''
+
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)
  
−
AI2 currently has projects in the following areas:
+
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.
  
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* Language and Vision
 
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* Information extraction and semantic parsing
 
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* Question answering
 
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* Language and reasoning
 
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* Machine learning and theory formation
 
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* Semantic search
 
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* Natural language processing
 
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* Diagram understanding
 
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* Visual knowledge extraction and visual reasoning
 
  
−
And more….  
+
'''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.
  
−
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.
 
  
−
'''Applicant'''
+
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
  
−
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.  
+
* 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]
  
−
'''Why AI2'''
+
'''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)
  
−
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:
+
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.
  
−
* 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;
+
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).
−
* 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;
 
−
* 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;
 
−
* 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;
 
−
* 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;
 
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* We are friendly – chances are you will like every one of the 30+ (and growing!) people who work here. We do!
 
  
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'''Application Process'''
+
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.
  
−
Visit our website for more information: http://allenai.org/jobs.html
+
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
  
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==Software Engineer  - Machine Learning / NLP (Chinese) at SYSTRAN==
+
'''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
  
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* Employer: SYSTRAN
+
'''Job Details'''
−
* Title: Software Engineer
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* 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.
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* Topics: Machine Learning, Natural Language Processing, Machine Translation
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* Start date is negotiable, but anticipated for Summer/Fall 2017.
−
* Location: San Diego
+
* 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.
−
* Deadline: Open until filled
 
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* Date Posted: January 29, 2016
 
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* Contact: Apply directly at https://recruit.systrangroup.com/recruit/Portal.na
 
  
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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.
+
'''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.
  
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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.
+
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.
  
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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.
+
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].
  
−
'''Key Qualifications'''
+
'''Questions''' <br/>
−
* Knowledge of natural language processing field, including but not limited to, formal grammar, syntactic parsing and morphology
+
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
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* Good algorithmic knowledge of machine learning
 
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* Experience writing and debugging software
 
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* Strong communications skills
 
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* Ability to work well as part of a team
 
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* Fluent in English.
 
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* Fluent in Chinese is a plus
 
  
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'''Education and Experience'''
 
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* MS or Ph D  in Computational Linguistics / Computer Science or relevant field.
 
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* 2+ years work experience preferred
 
  
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'''Benefits'''
+
== Researcher in Machine Learning and NLP, DFKI, Germany ==
−
* Successful candidates will be offered a competitive salary based on their qualifications and experience.
 
  
 +
* 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]
  
−
==Vacancy for Lecturer/Senior Lecturer/Reader at University of Dundee==
+
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.
  
−
* Employer: University of Dundee
+
'''Key research responsibilities''' include:
−
* Title: Lecturer/Senior Lecturer/Reader
+
* machine and deep learning for natural language processing/machine translation
−
* Topics: Computational Linguistics, Language, Argumentation, Artificial Intelligence
+
* software development and integration
−
* Location: Dundee, UK
+
* publication in top-tier conferences and journals
−
* Deadline: 27 February 2016
 
−
* Date Posted: 12 January 2016
 
−
* Contact: Prof. Chris Reed (see http://arg.tech/lecturer)
 
  
−
£34,576 to £55,389 Full Time, Permanent
+
'''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
  
−
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.
+
'''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
  
−
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.
+
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).
  
−
'''Summary of Job Purpose and Principal Duties'''
+
'''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.
  
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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
+
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.
−
group can be found in the Further Particulars.
 
  
−
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
+
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.
−
Fellowships.
 
  
−
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.
+
'''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.
  
−
'''Job Summary'''
+
'''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.
  
−
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:
+
'''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.
  
−
* Contribute to the ongoing research in one of the three research groups described above.
 
−
* Contribute to the generation of external research funding.
 
−
* Publish in high quality research journals and major international conferences.
 
−
* Teach at undergraduate and post-graduate level.
 
−
* Supervise students at all levels (honours and MSc projects, PhD).
 
−
* Undertake administrative duties.
 
  
−
'''Application Requirements'''
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
  
−
In addition to the online form, applicants must include with their application:
+
* 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]
  
−
* Cover letter outlining fit to role.
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
−
* Research plan (1-2 pages) covering proposed research over the first three years of the appointment.
 
−
* Teaching plan (1-2 pages) outlining fit to current teaching at Dundee and teaching methodology.
 
  
 +
'''Associate Research Scientist'''<br />
 +
'''(PostDoc- or PhD-level; for an initial term of two years)'''
  
−
==Postdoctoral Fellow in Computational Models of Reasoning / Intelligence Systems Section at AI Center / US Naval Research Laboratory==
+
to strengthen the group’s profile in the areas of Interactive Machine
−
* Employer: US Naval Research Laboratory
+
Learning (IML) or Natural Language Processing for Language Learning.
−
* Title: Postdoctoral Research Fellow
+
The UKP Lab is a research group comprising over 30 team members who
−
* Topics: Reasoning, Computational Modeling, Language, Artificial Intelligence
+
work on various aspects of Natural Language Processing (NLP), of
−
* Location: Washington, DC
+
which Interactive Machine Learning and Natural Language Processing
−
* Deadline: Open until filled
+
for Language Learning are the focus areas researched in collaboration
−
* Date Posted: January 20, 2016
+
with partners in research and industry.
−
* Contact: Sunny Khemlani (sunny.khemlani@nrl.navy.mil)
 
  
−
'''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.
+
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.
  
−
'''Supervisor''': Sunny Khemlani, PhD
+
* 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.
  
−
'''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.
+
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.
  
−
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance.
+
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.
  
−
'''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.
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
−
'''To apply''': Send a cover letter and CV to Dr. Sunny Khemlani at sunny.khemlani@nrl.navy.mil.
+
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 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
  
−
==Internship positions available at Juji, Inc.==
+
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: Juji, Inc.
+
−
* Title: Intern
+
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.
−
* Location: Saratoga, CA
+
   
−
* Deadline: open until all the positions are filled
+
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.
−
* Date Posted: January 14, 2016
 
−
 
 
−
'''Description''':
 
−
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.   
 
−
 
 
−
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.
 
−
 
 
−
We have multiple positions on two main tracks:
 
−
 
 
−
* 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.
 
−
 
 
−
* 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.
 
−
 
 
−
'''Qualifications'''
 
−
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.  
 
−
 
 
−
'''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.  
 
 
   
 
   
 +
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
  
−
==Postdoctoral Fellow in Natural Language Processing / AI at Brigham and Women's Hospital / Harvard Medical School==
+
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.  
−
* Employer: Brigham and Women's Hospital / Harvard Medical School
 
−
* Title: Postdoctoral Research Fellow
 
−
* Topics: Natural Language Processing, Artificial Intelligence, Predictive Modeling
 
−
* Location: Boston, MA
 
−
* Deadline: Open until filled
 
−
* Date Posted: January 8, 2016
 
−
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)
 
−
 
 
−
'''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.
 
−
 
 
−
'''Supervisor''': Alexander Turchin, MD, MS, FACMI
 
−
 
 
−
'''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.
 
−
 
 
−
'''Education''': PhD in computer science, biomedical informatics, linguistics, or a related discipline; MD or an equivalent degree.
 
−
 
 
−
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.
 
−
 
 
−
'''Available''': Immediately.
 
−
 
 
−
'''Compensation''': according to NIH (NRSA) stipend levels.
 
−
 
 
−
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.
 
−
 
 
−
==Internship positions available in Natural Language Processing at Adobe Research==
 
−
* Employer: Adobe Systems Incorporated
 
−
* Title: NLP Scientist Intern
 
−
* Natural Language Processing, Machine Learning, Question Answering and Dialog Systems.
 
−
* Location: San Jose, CA
 
−
* Deadline: open until all the positions are filled
 
−
* Date Posted: December 23, 2015
 
−
* Trung Bui: bui@adobe.com
 
−
 
 
−
'''Description''':
 
−
We are looking for several NLP scientist interns who will work on semantic understanding, question answering and dialog systems to improve Adobe digital media and digital marketing products.
 
−
The internship will be at the Medial Intelligence Lab under the Imagination Lab at Adobe Research (http://www.adobe.com/technology.html) located in San Jose, California. It is 13 weeks long and can start any time from March 1, 2016.
 
−
 
 
−
'''Key Qualifications'''
 
−
*Experience with semantic parsing, question answering and dialog systems.
 
−
*Experience with machine learning, deep learning.
 
−
*Good programming skills in Java/C++ and/or Python
 
−
 
 
−
'''Education'''
 
−
M.S. or PhD student in Computer Science or related field
 
−
 
 
−
'''Additional Requirements'''
 
−
No.
 
−
 
 
−
== Associate Research Scientist at UKP Lab, TU Darmstadt ==
 
−
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], Department of Computer Science, Technische Universität Darmstadt
 
−
* Title: Associate Research Scientist
 
−
* Speciality: Natural Language Processing
 
−
* Location: Darmstadt, Germany
 
−
* Deadline: January 15, 2016
 
−
* Date posted: December 23, 2015
 
−
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
 
−
 
 
−
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.
 
−
 
 
−
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.
 
−
 
 
−
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.
 
−
 
 
−
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 15 January 2016. The position is open until filled. Later applications may be considered if the position is still open.
 
−
 
 
−
== Postdoctoral Researcher position in NLP/Computational Social Science at UPenn ==
 
−
* Employer: Computer & Information Science, University of Pennsylvania, USA
 
−
* Title: Postdoctoral Researcher
 
−
* Speciality: Natural Language Processing, Computational Social Science
 
−
* Location: Philadelphia, USA
 
−
* Deadline: January 15, 2016
 
−
* Date posted: December 21, 2015
 
−
* Contact: applications@wwbp.org
 
−
 
 
−
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.
 
−
 
 
−
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.
 
−
 
 
−
* Application Deadline: January 15, 2015
 
−
* Approximate Start Date: March 1, 2016 (but flexible)
 
−
 
 
−
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.
 
−
 
 
−
The University of Pennsylvania is an EOE/Affirmative Action Employer. Position contingent on funding.
 
−
 
 
−
Primary Contact: Professor Lyle Ungar, ungar@cis.upenn.edu
 
−
 
 
−
 
 
−
== Multiple positions as Full-time researcher, Post-doc researcher, Software Engineer and Summer Intern in IBM Research - Almaden, San Jose ==
 
−
* Employer: IBM Research - Almaden
 
−
* Title: Researcher, Software Engineer, Post-doc, Summer Intern
 
−
* Speciality: natural language processing, information integration, entity resolution, machine learning, ontologies, and large-scale data management
 
−
* Location: San Jose, CA
 
−
* Deadline: (until filled)
 
−
* Date posted: December 18, 2015
 
−
* Contact: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)
 
−
 
 
  
−
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:
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
−
* creation, maintenance and evolution of ontologies to capture domain concepts of interest
 
−
* 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
 
−
* 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
 
−
* 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
 
−
* easy-to-use knowledge consumption interfaces for both human and machine consumption including support for  discovery and ad-hoc NLQ driven interfaces
 
−
* incorporating crowd sourcing and continuous evolution of the system through learning from user interactions.
 
  
 +
'''Essential criteria'''
  
−
The research builds upon and extends successful projects from our group, which have resulted in academic, industrial and open source impact:
+
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
−
* SystemT: http://researcher.watson.ibm.com/researcher/view_group.php?id=1264
+
* 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.
−
* Midas: http://researcher.watson.ibm.com/researcher/view_group.php?id=2171
+
* A strong background in statistics and linear algebra.
−
* SystemML: http://researcher.watson.ibm.com/researcher/view_group.php?id=3174
+
* 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'''
  
−
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).
+
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.  
−
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.  
 
  
 +
'''Background about the project'''
  
−
Please send your resumes to: Laura Chiticariu (chiti {at} us.ibm.com) and/or Lucian Popa (lpopa {at} us.ibm.com)
+
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.
  
−
== Two Postdoc Opportunities at the US Army Research Lab in the Washington, DC Metro Area ==
+
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: US Army Research Laboratory
 
−
* Title: Postdoctoral Fellow
 
−
* Speciality: Knowledge Representation, Knowledge Bases, Common-Sense Reasoning, Planning
 
−
* Location: Adelphi, MD
 
−
* Deadline: (until filled)
 
−
* Date posted: November 30, 2015
 
−
* Contact: douglas.a.summers-stay.civ@mail.mil and/or ethan.a.stump2.civ@mail.mil
 
  
−
The US Army Research Laboratory currently has two postdoc opportunities:
+
'''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.
  
−
'''Position #1'''
+
==  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 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.
+
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.
  
−
The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.
+
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.
  
−
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.
+
'''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.
  
−
'''Position #2'''
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
−
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.
+
'''Research Team'''
  
−
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.
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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”.
  
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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.
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Informal enquiries:  Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).  
  
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The position is available immediately with a duty location at the Adelphi Laboratory Center (ALC), Adelphi, MD.
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Deadline of applications: 13/03/2017
  
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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.
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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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