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** ETS (Educational Testing Service)
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** Senior Research Scientist, Natural Language Processing
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** Research
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* '''[[Instructions for Posting Job Ads]]'''
** Princeton, New Jersey, United States, 08540
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* See also the [http://linguistlist.org/jobs Linguist Job List].
** 3/31/2011
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* Archived postings:
** 3/01/2011
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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]]
** http://www.Click2Apply.net/dm5y53s
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<!-- USE "SHOW PREVIEW" TO VERIFY YOUR EDITS -->
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<!-- INSERT YOUR JOB AD IMMEDIATELY BELOW THIS HEADER -->
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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]
 +
 
 +
 
 +
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 .
 +
 
 +
 
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== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
 +
* 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]
  
<p><strong>ETS (Educational Testing Service</strong>), with headquarters in Princeton, NJ, is a global $1.3B not for profit organization. Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development. As a nonprofit corporation and an innovator in developing tests for clients in education, government and business, we are dedicated to advancing educational excellence for the communities we serve.</p> <p>In the context of this position, we will turn to your skills and scientific/technical expertise to conceptualize, design, obtain support for, conduct and manage major research and/or development projects, particularly those in which natural language processing (NLP) techniques are applied to problems in education or assessment. Your responsibilities would include planning a long-term substantive research agenda, designing/conducting complex scientific studies, disseminating results and implications of projects and functioning as an expert in the major facets of the program. This position further offers the opportunity to generate or contribute to new or modified NLP theories and methodology and provide leadership for the development of new products or services for education and for the conduct of major projects in automated scoring and NLP.</p><p>Our qualifications include:</p> <ul> <li>A Ph.D in Natural Language Processing, Computational Linguistics or Computer Science</li> <li>Eight years of independent research experience providing evidence of continuing and substantial contributions to a field of study</li> <li>A strong statistical and machine learning background</li> <li>Demonstrable contributions to new and/or modified theories of Natural Language Processing and their implementation in automated systems</li> <li>Practical expertise with NLP tools and fluency in at least one major programming language (e.g. Java, Perl, C/C++, Python)</li> <li>The ability to lead the development of proposals for major research, development, or large-scale NLP projects,</li> <li>Ability to develop, promote and maintain professional relationships as representative, consultant or advisor to external advisory or policy boards and councils, research organizations, educational institutions and educators </li> <li>Familiarity with the application of NLP tools to educational problems</li> <li>Demonstrated ability to lead project teams and to work collaboratively with a diverse set of contributors</li> </ul> <p>We offer a competitive salary and excellent compensation package including medical, dental, vision, 403(b) retirement plan, life and disability insurance, paid time off and an employee assistance program. <strong>Please apply online at: [http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=104122&type=&cfcend http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=104122&type=&cfcend]</strong></p> <p>EOE</p><br><b>[http://www.Click2Apply.net/dm5y53s Apply Here]
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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'''<br>
 +
'''(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.
  
* Archived postings:
+
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.
** [[Employment opportunities posted 2010]]
+
 
** [[Employment opportunities posted 2009]]
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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.
** [[Employment opportunities posted 2008]]
+
 
** [[Employment opportunities posted 2007]]
+
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).
 +
 
 +
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.
 +
 
 +
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297
 +
We look forward to receiving your application!
 +
 
 +
 
 +
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
 +
 
 +
* Employer: Cardiff University
 +
* Title: Postdoctoral Research Associate
 +
* Specialty: vector space embeddings, statistical relational learning, knowledge representation, neural networks, explainable AI
 +
* Location: Cardiff, UK
 +
* Deadline: May 20, 2017
 +
* Date posted: April 20, 2017
 +
* Contact: [mailto:schockaerts1@cardiff.ac.uk Steven Schockaert]
 +
 
 +
Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:
 +
* The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.
 +
*The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval.
 +
 
 +
Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)
 +
 
 +
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available.
 +
 
 +
 
 +
'''More information'''
 +
For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.
 +
 
 +
 
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== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
 +
 
 +
* Employer: University of Colorado Boulder
 +
* Title: Postdoctoral Research Associate
 +
* Specialty: Advanced Machine Learning
 +
* Location: Boulder, Colorado, United States
 +
* Deadline: Ongoing, desired start Summer/Fall 2017
 +
* Date posted: March 31, 2017
 +
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
 +
 
 +
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
 +
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
 +
 
 +
The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time  postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.
 +
 
 +
The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).
 +
 
 +
The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.
 +
 
 +
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.
  
== Text Mining and Natural Language Processing Specialists for eBay ==
+
'''Required'''
** Employer: eBay
+
* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)
** Rank: Applied Researcher
+
* 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)
** Speciality: Information Retrieval & Text Mining / NLP
+
* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record
** Location: San Jose, CA, USA
 
** Deadline: Until filled
 
** Date Posted: 2/25/2011
 
** Contact email: smohan@ebay.com
 
eBay is looking for experts in web-scale Information Retrieval and Text Mining / Natural Language Processing to join the Search Science team.
 
  
Bring your ideas, energy, and dedication to improve search experience on eBay.  The world class search engine at the heart of eBay serves more than 350 million queries every day.  The Search Science team is passionate about building the query services and relevance factors that will match our users’ needs to the products in the world's largest online marketplace, and we are looking for top-notch applied researchers.
+
'''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.
  
'''QUALIFICATIONS'''
+
'''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.
  
·        Ph.D. in Computer Science or related field plus 4 years of relevant software industry R&D experience required.
+
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.
  
·        Expertise in Information Retrieval and Nature Language Processing.
+
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].
  
·        Strong statistical and machine learning background.
+
'''Questions''' <br/>
 +
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
·        Experience and proficiency in Java and/or C++, Perl or similar scripting languages, and distributed processing of documents and web logs using Hadoop.
 
  
·        Track record of deploying cutting edge technology in an industrial setting.
+
== Researcher in Machine Learning and NLP, DFKI, Germany ==
  
'''JOB REQUIREMENTS'''
+
* 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]
  
·        Use your knowledge, skills, and passion for improving search to find opportunities in eBay's log data and search results.
+
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.
  
·        Use deep domain expertise to individually drive innovative ideas.
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'''Key research responsibilities''' include:
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* machine and deep learning for natural language processing/machine translation
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* software development and integration
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* publication in top-tier conferences and journals
  
·        Participate in brainstorming and discovery exercises to determine new ideas.
+
'''General responsibilities''' include:
 +
* engagement with industry partners and contract research
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* identification of funding opportunities and engagement in proposal writing
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* contribution to teaching and supervision in accordance with University and DFKI rules and regulations
 +
* administrative work associated with programmes of research
  
·        Build experimental frameworks and gather data from across the company to support your work.
+
'''Requirements:'''
 +
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar
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* 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
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* Command of German and other  languages not a requirement but helpful
  
·        Conduct experiments, write prototypes, write specifications, and optionally write production code to deploy new features and methods that improve search quality.
+
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).
  
·        Lead projects and collaborate with other researchers, engineers, and product teams to develop strategic and tactical enhancements to search.
+
'''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.
  
·        Provide technical leadership and mentoring to other team members.
+
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.
  
·        Lead and contribute to multiple small team projects.
+
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.
  
·        Communicate your methodology and results to a community of researchers, developers, analysts, and product managers working in search. Communicate to technical and nontechnical audiences inside and outside the search team.
+
'''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.
  
·        Participate in meetings with other eBay groups to document best practices and facilitate a knowledge base.
+
'''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 [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.
  
  
== Freelance British English, Japanese, and Mexican Spanish computational linguists==
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
** Employer: The Lingua Team
 
** Rank: Freelance contractor
 
** Speciality: Speech & Natural Language Processing
 
** Location: Seattle, WA (work can be done remotely)
 
** Deadline: 5/1/2011
 
** Date Posted: 2/12/2011
 
** Contact email: http://www.thelinguateam.com
 
The Lingua Team, a company based in the Seattle area, dedicated to linguistic services is always looking for a computational linguists with native or near native knowledge of the most common languages to do freelance work remotely. Please, visit our site and email your resume for consideration.
 
  
== French computational linguist==
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
** Employer: The Lingua Team
+
* Title: Associate Research Scientist
** Rank: Language support contractor
+
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
** Speciality: Speech recognition
+
* Location: Darmstadt
** Location: Seattle, WA (work can be done remotely)
+
* Deadline: March 8, 2017
** Deadline: 03/04/2011
+
* Date posted: February 21, 2017
** Date Posted: 12/28/2010
+
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]
** Contact email: http://www.thelinguateam.com
 
The Lingua Team, a Seattle area based company, dedicated to linguistic services is looking for a French computational linguist to create computational grammars in xml format. Knowledge of French is a must. Please, email your resume for consideration.
 
  
 +
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
  
== Senior Research Assistant, Natural Language Processing ==
+
'''Associate Research Scientist'''<br />
** Employer: ETS (Educational Testing Service)
+
'''(PostDoc- or PhD-level; for an initial term of two years)'''
** Speciality: Research
 
** Location: Princeton, New Jersey 08540
 
** Date Posted: 02/21/2011
 
** Please apply online: http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=100522&type=True&cfcend
 
  
 +
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.
  
<p><strong>ETS (Educational Testing Service)</strong>, with headquarters in <strong>Princeton, NJ</strong>, is a global $1.3B not for profit organization.  Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development. As a nonprofit corporation and an innovator in developing tests for clients in education, government and business, we are dedicated to advancing educational excellence for the communities we serve.</p>
+
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.
  
<b>Job Description:</b>
+
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.
  
Educational Testing Service has an opening for a Senior Research Assistant position in the Applied Research and Development Group. The successful candidate will primarily provide support to Research Scientists working on a branch of computer science and computational linguistics known as Natural Language Processing (NLP) by assisting in all phases of research projects, including research design, project management, data collection and analysis. He or she will also collaborate with researchers in preparing study results for publication or presentation, including literature searches, producing charts and graphs, writing and editing.</p>
+
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:
 +
[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.
  
<b>Basic Functions and Responsibilities:</b>
+
==  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
  
Coordinate research project workflow including planning and designing pilot and field testing; data collection, analysis, and presentation; preparation, production, and distribution of proposals and reports; maintaining data files; and producing workshop materials. Schedule services with other ETS departments and project staff. Act as liaison between project directors and field staff, support staff, and research community, as assigned. Plan, manage, and perform annotations for a variety of projects.
+
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.
  
<ul>
+
==  Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==
<li>Collect, organize, and verify data; analyze, synthesize, and interpret data; perform statistical calculations.
+
*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
  
<li>Monitor activities of temporary and support staff and data collection centers to control budgets, workflow, quality of coding operations, and project activities.
+
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.  
  
<li>Develop coding systems, procedures, and manuals; research instruments; statistical analyses; and files of current resource materials for workshops and projects.
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
  
<li>Write, revise, edit, and proofread research instruments, project documents and publications, memoranda, and correspondence.
+
'''Essential criteria'''
  
<li>Contribute to formal reports and proposals (or sections thereof).
+
* 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.
  
<li>Update publications and prepare graphics, tables, charts, graphs, figures, and visual aids. Administer tests, research instruments, interviews, and surveys.
+
'''Background about the university'''
  
<li>Conduct literature searches and prepare reference lists, evaluating and selecting materials to be included.
+
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.  
  
<li>Operate computer terminal to enter, edit, and update data; program and utilize sophisticated statistical packages for data analysis; act as data custodian for cost center.
+
'''Background about the project'''
  
<li>Select and train field staff; instruct support staff.
+
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.  
  
<li>Arrange and attend meetings with clients, committees, and consultants.
+
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.
  
<li>Meet with clients to plan or interpret guidelines, as assigned.
+
'''More information'''
</ul>
 
  
 +
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.
  
<b>Required Experience:</b>
+
==  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
  
<p>EDUCATION A Bachelor's degree in a behavioral or social science with coursework in Statistics is necessary. Coursework or experience working in linguistics, computer science and/or natural language processing (NLP) technologies preferred.</p>
+
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.
  
<p>EXPERIENCE A successful candidate will have exemplary written, grammatical, and technical skills. Three years of research-related experience in an academic or professional setting is necessary.
+
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.
</p>
 
  
 +
'''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'''
  
== Associate Research Engineer, Natural Language Processing ==
+
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”.
** Employer: ETS (Educational Testing Service)
 
** Speciality: Research
 
** Location: Princeton, New Jersey 08540
 
** Date Posted: 01/07/2011
 
** Link to website: http://www.Click2Apply.net/xymwg8p
 
  
<p><strong>ETS (Educational Testing Service)</strong>, with headquarters in <strong>Princeton, NJ</strong>, is a global $1.3B not for profit organization. Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development. As a nonprofit corporation and an innovator in developing tests for clients in education, government and business, we are dedicated to advancing educational excellence for the communities we serve.</p> <p>In this team-oriented role, the selected candidate will assist with the implementation of natural language processing (NLP) components of medium- to large-scale, complex research projects for ETS researchers, testing program areas and external clients. You will be offered the opportunity to consult with research scientists in the application, modification, and documentation of such systems and contribute to the implementation and support of new NLP methodologies to support research system development.</p> <p>Be prepared to further assist in the preparation of NLP development components of proposals and cost/resource estimates, implement components of technical documentation of NLP software systems, solutions and results and regularly attend area-wide staff training and development sessions.</p><p>In addition to exceptional verbal/written communication skills, our qualifications include:</p> <ul> <li>Master's degree in Computer Science, NLP, Language Technology, Computational Linguistics, Linguistics or a closely related field</li> <li>A strong programming background, in languages such as Perl, Java, Python, and C, and facility with computational algorithms are essential</li> <li>Coursework in statistics and experience in using machine learning toolkits are highly desirable</li> <li>Ability to maintain continuing awareness of recent advances in natural language processing (including speech processing), machine learning, and software development methodologies</li> <li>Knowledge of UNIX and Windows computing environments</li> <li>Familiarity with UNIX tools and scripting languages and  algorithms, methods and data structures in common use in the processing of speech and language data</li> </ul> <p>We offer a competitive salary and excellent compensation package including medical, dental, vision, 403(b) retirement plan, life and disability insurance, paid time off and an employee assistance program. Please apply online at:</p> <p>[http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=99822&type=&cfcend http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=99822&type=&cfcend]</p> <p>EOE</p><p>[http://www.Click2Apply.net/xymwg8p Apply Here]
+
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).  
  
== Associate Research Scientist, Speech ==
+
Deadline of applications: 13/03/2017
** ETS (Educational Testing Service)
 
** Research
 
** Princeton, New Jersey, United States, 08540
 
** 02/06/2011
 
** 01/07/2011
 
** http://www.apply-for-job.net/c/jobclick.cfm?site=10875&job=7348049
 
  
<strong>ETS (Educational Testing Service),</strong> with headquarters in Princeton, NJ, is a global $1.3B not for profit organization.  Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development. As a nonprofit corporation and an innovator in developing tests for clients in education, government and business, we are dedicated to advancing educational excellence for the communities we serve.</p> <p>In this integral position, the selected candidate will apply their scientific and technical skills to conceptualize, design, obtain support for, conduct, manage and disseminate the results of research projects in the field of automated speech assessment, or portions of large-scale research studies or programs in the same field. <br /><br />You will be offered the opportunity to develop and/or modify theories to conceptualize and implement new capabilities in automated scoring and speech-based analysis and evaluation systems used to improve assessments, learning tools and test development practices. Be prepared to design/conduct research studies and capability development, oversee select portions of research proposals and project budgets and function as an expert in major facets of the projects.</p><p>Our requirements include:</p> <ul> <li>Ability to participate in dissemination activities through the publications of research papers, progress and technical reports, the presentation of seminars or other appropriate communication vehicles</li> <li>Must be able to develop professional relationships as a representative, consultant or advisor to external advisory and policy boards and councils, research organizations, educational institutions and educators </li> <li>Ph.D. in Computational Linguistics, Computer Science, Electrical Engineering or related areas, with strong emphasis on speech technology, natural language processing, and machine learning, and preferably some education in linguistics </li> <li>Evidence of substantive research experience and/or experience in developing and deploying speech capabilities</li> <li>Demonstrable contributions to new and/or modified theories of speech processing and their implementation in automated system</li> <li>Expertise in the application of speech recognition systems and fluency in at least one major programming language (e.g. Java, Python, Perl), as well as strong experience in Unix scripting</li> </ul> <p>We offer a competitive salary and excellent compensation package including medical, dental, vision, 403(b) retirement plan, life and disability insurance, paid time off and an employee assistance program. Please apply online at: </p> <p>[http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=97431&type=&cfcend http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=97431&type=&cfcend]</p> <p>EOE</p>[http://www.apply-for-job.net/c/jobclick.cfm?site=10875&job=7348049 Apply Here]
+
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