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

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* Please post your job ad below.
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* Jobs are listed in chronological order of posting: '''first is newest, last is oldest'''.
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* '''[[Instructions for Posting Job Ads]]'''
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* '''Please remove your posting when the position is filled.'''
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* See also the [http://linguistlist.org/jobs Linguist Job List].
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* Please include the following information:
 
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** Employer
 
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** Rank or Title
 
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** Specialty (e.g., Computational Linguistics, Natural Language Processing, Machine Translation)
 
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** Deadline
 
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** Date Posted
 
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** Contact email or link to website
 
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* See also the [http://linguistlist.org/jobs/index.html Linguist Job List].
 
 
* Archived postings:
 
* Archived postings:
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** [[Employment opportunities posted 2008]]
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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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** [[Employment opportunities posted 2007]]
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== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==
  
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* 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]
  
  
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== Scientist I ==
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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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{|
 
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| '''Employer:'''        ||Web Intelligence Division, J.D. Power and Associates (McGraw-Hill)
 
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|-
 
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| '''Title, Rank:'''      ||Scientist I.
 
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|-
 
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| '''Specialty:'''        ||Machine Learning, Computational Linguistics, Natural Language Processing.
 
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|-
 
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| '''Location:'''        ||Boulder, Colorado.
 
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|-
 
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| '''Start date:'''      ||The position is available immediately.
 
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|-
 
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| '''Date Posted:'''      ||May 1st, 2009.
 
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|-
 
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| '''Links to website:''' ||http://www.jdpowerwebintelligence.com
 
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|-
 
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| '''Contact:'''          ||Nicolas Nicolov <nicolas_nicolovNOSPAM@jdpa.com> [remove six chars]
 
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|}
 
  
 +
== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
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J.D.Power and Associates is growing and hiring top-notch scientists to develop cutting-edge web mining technology. Our science team is working on advanced text analysis of vast amounts of data, scalable information retrieval, learning semantic concepts and lots of cool new stuff.
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* 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]
  
 +
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a
  
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'''Requirements:'''
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'''Scientific System Developer'''<br>
 +
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
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* Recent Ph.D. in Machine Learning, Computational Linguistics, Artificial Intelligence, Computer Science or equivalent.
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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.  
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* Strong statistical, natural language processing, machine learning background with emphasis on coreference, meronymy, dependency parsing, sentiment/opinion analysis, text clustering and categorization, graph analysis.
 
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* Experience with scientific computing on large datasets, natural language processing, information extraction, information retrieval, multilingual datasets, distributed systems is a plus.
 
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* Strong experience with C++/Java, Scala/Ruby/Python development of large software systems, Linux/Windows environments.
 
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* Proven track record of publications/patents preferred.
 
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* Strong verbal and written communication skills.
 
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* At least 4 years of research experience (relevant university experience - ok).
 
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* Enthusiasm for solving challenging problems.
 
  
 +
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.
  
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'''Contact:''' Nicolas Nicolov <nicolas_nicolovNOSPAM@jdpa.com> [remove six chars]
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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.
  
 +
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).
  
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== Research Position in Computational Linguistics at Austrian Research Institute for AI (OFAI), Vienna ==
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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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* '''Employer:''' OFAI, Vienna, Austria
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Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297
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* '''Title:''' Researcher
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We look forward to receiving your application!
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* '''Specialty:''' Computational Linguistics
 
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* '''Deadline:''' April 15, 2009
 
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* '''Date Posted:''' March 30, 2009
 
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* '''Links to website:''' [http://www.ofai.at/research/nlu/]  
 
  
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The Austrian Research Institute for Artificial Intelligence (OFAI)
 
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in Vienna, Austria offers two research positions in its Language
 
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Technology group.
 
  
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Candidates are expected to have a degree in computational linguistics
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== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
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or computer science with a background in language technology.
 
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She/he will be an open minded team worker, who is able
 
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to work creatively in an interdisciplinary context. She/he will have
 
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good programming skills and be able to flexibly use different
 
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programming languages. She/he likes to to work in a research environment
 
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constantly learning and developing fresh concepts and ideas.
 
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Publishing research results is part of the job and actively encouraged.
 
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The successful candidates will have a strong background in one or more of
 
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the following areas: ontology engineering, semantic systems, text mining
 
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and machine learning.
 
  
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Fluency in English is expected.
+
* 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]
  
−
Both positions are in the framework of a project aiming at advancing
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Applications are invited for two Postdoctoral Research Associate posts at Cardiff University’s School of Computer Science & Informatics:
−
speech recognition by the integration of (context-dependent) semantic
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* 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.
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knowledge. The project is ongoing and will continue until April 2010.
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*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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Contracts will be for the duration of the project.
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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)
−
Continued employment after the end of the project is possible.
 
  
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Depending on academic credentials and experience of the candidate,
+
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.  
−
the yearly gross salary will be in the range of EUR 42000 - 54000.
 
  
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Both positions are to be filled asap.
 
  
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Please mail applications including a CV to Harald Trost <harald.trost@ofai.at>
+
'''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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==Postdoctoral Fellowship at the Institut de Recherche en Informatique de Toulouse (IRIT) Université de Toulouse 3==
 
  
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Subject : Applying learning techniques to discourse analysis
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== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
  
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Période : 12 months, September 2009 -> August 2010
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* 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]
  
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Context :
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'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
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This postdoctoral fellowship, is part of the ANR project
+
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
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ANNODIS, which includes the labs: IRIT (Université de Toulouse 3), CLLE (Université
 
−
de Toulouse 2), and GREYC Université de Caen).  The goal of this project is to
 
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build a corpus of French texts annotated with discourse structure at several levels.  The project also has the goal of providing automatic and semi-automatic tools for helping with this task.
 
  
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The postdoctoral fellow will be a member of the IRIT lab at l'université de Toulouse 3, Toulouse, in the research group Lilac under the direction of
+
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.
−
Nicholas Asher.
 
  
−
Objectives :
+
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).
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Based on the data culled from the manual annotation of our corpus, the first objective of the postdoctoral fellow will be to design and supervise experiments for the automatic recovery of the discourse structure of a text and to evaluate the feasibility of semi supervised and supervised learning strategies given the data in the corpus. A discourse structure is a graph where the nodes are text segments and the arcs are discourse relations. Thus, the extraction task  has three stages: 1) finding the segments, 2) determining the attachment points for segments in the graph et 3) determining the discourse relation or relations between the attached segments.
 
  
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The postdoctoral fellow will also be in charge of the final collection and organization of the manual annotation data.
+
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.
  
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Candidate should have:
+
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.
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- a Ph.D.
 
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- competence in NLP and/or information extraction, and automated learning methods.
 
  
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A familiarity with theories of discourse structure would be a Plus.
+
'''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
  
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Salary: 3000 euro per month
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'''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.
  
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Candidates should send a dossier with a detailed CV (pdf) by email to:
+
'''How to apply''' <br/>
−
asher@irit.fr AND muller@irit.fr.
+
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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== Post-Doctoral Position in Computational Linguistics at Uppsala University ==
+
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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* '''Employer:''' Uppsala University, Sweden
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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].
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* '''Title:''' Research Fellow
 
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* '''Specialty:''' Computational Linguistics
 
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* '''Deadline:''' April 24, 2009
 
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* '''Date Posted:''' March 17, 2009
 
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* '''Links to website:''' [http://stp.lingfil.uu.se/~nivre/docs/PostdocUU.pdf | Post-Doc Position]
 
  
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This is a full-time, limited-term position that can maximally be extended up to four
+
'''Questions''' <br/>
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years. The position involves a small amount of teaching and supervision but is mainly
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Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
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devoted to research. The deadline for applications is April 14, 2009. For more
 
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information, contact Joakim Nivre <joakim.nivre@lingfil.uu.se>.
 
  
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== Research Positions, Human Language Technology Center of Excellence ==
 
  
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* '''Employer:''' Human Language Technology Center of Excellence (at Johns Hopkins University)
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== Researcher in Machine Learning and NLP, DFKI, Germany ==
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* '''Titles:''' Postdoctoral researchers, research staff, professors on sabbaticals, visiting scientists
 
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* '''Specialty:''' Speech and Natural Language Processing
 
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* '''Deadline:''' April 1, 2009
 
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* '''Date Posted:''' March 12, 2009
 
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* '''Links to website:''' [http://web.jhu.edu/HLTCOE/opportunities.html | Research Position]
 
  
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The Human Language Technology Center of Excellence (COE) at the Johns Hopkins University is seeking to hire outstanding Ph.D. researchers in the field of speech and natural language processing. The COE seeks the most talented candidates for both junior and senior level positions including, but not limited to, full-time research staff, professors on sabbaticals, visiting scientists and post-docs. Candidates will be expected to work in a team setting with other researchers and graduate students at the Johns Hopkins University, the University of Maryland College Park and other affiliated institutions.
+
* 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]
  
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Candidates should have a strong background in one of the following areas:
+
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.
  
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- NATURAL LANGUAGE PROCESSING: Information extraction, knowledge distillation, machine translation, semantic annotation, text processing, etc.
+
'''Key research responsibilities''' include:
 +
* machine and deep learning for natural language processing/machine translation
 +
* software development and integration
 +
* publication in top-tier conferences and journals
  
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- SPEECH PROCESSING: Robust speech recognition across language channel, formal vs. informal genres, speaker identification, language identification, speech retrieval, spoken term detection, etc.
+
'''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
  
−
- MACHINE LEARNING: Learning on very large datasets and streams for text and/or speech, feature extraction, domain adaptation, semi-supervised learning
+
'''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 COE was founded in January 2007 and has a long-term research contract as an independent center within Johns Hopkins University. Located next to Johns Hopkins’ Homewood Campus in Baltimore, Maryland, the COE’s distinguished contract partners include the University of Maryland College Park, the Johns Hopkins University Applied Physics Lab, and BBN Technologies of Cambridge, Massachusetts.  World-class researchers at the COE focus on fundamental challenge problems critical to finding solutions for real-world problems of importance to our government sponsor. The COE offers substantial computing capability for research that requires heavy computation and massive storage. In the summer of 2009, the COE will hold its first annual Summer Camp for Advanced Language Exploration (SCALE), inviting the best and brightest researchers to work on common areas in speech and NLP. Researchers are expected to publish in peer-reviewed venues.
+
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).
  
−
Applicants should have earned a Ph.D. in Computer Science or a closely related field. Applicants should submit a curriculum vitae, research statement, names and addresses of at least four references, and an optional teaching statement. Please send applications and inquiries about the position to hltcoe-hiring@jhu.edu.
+
'''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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While applications will be evaluated as received until the position is filled, applicants are strongly encouraged to indicate intent to apply by contacting the center before April 1, 2009. U.S. Citizenship is required and applicants should note citizenship status on their application. Additionally, security clearance is required and the COE will seek a clearance for those who do not already have one. The Johns Hopkins University is an equal opportunity employer and has a smoke-free environment.
+
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.
  
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== Chair and Lectureship in Computing Science, Aberdeen ==
+
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.
  
−
* '''Employer:''' University of Aberdeen
+
'''Geographical environment:'''
−
* '''Titles:''' Chair (full professor), Lecturer (assistant professor)
+
[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.
−
* '''Specialty:''' See full adverts. Areas include multi-modal interaction and natural language generation
 
−
* '''Deadline:''' April 13, 2009
 
−
* '''Date Posted:''' February 26, 2009
 
−
* '''Links to website:''' [http://www.abdn.ac.uk/jobs/display.php?recordid=NAT016A | Chair position] [http://www.abdn.ac.uk/jobs/display.php?recordid=NAT017A | Lectureship position] [http://www.csd.abdn.ac.uk/research | Research at Aberdeen]
 
  
−
== Natural Language Generation Group, The Open University: Research Associate, Text-to-Text Generation/Dialogue ==
+
'''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.
  
−
* '''Employer:''' The Open University
+
'''Application:'''
−
* '''Title:''' Research Associate
+
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.
−
* '''Specialty:''' Text-to-Text Generation/Dialogue
 
−
* '''Deadline:''' February 15, 2009
 
−
* '''Date Posted:''' February 3, 2009
 
−
* '''Link to website:''' [http://www3.open.ac.uk/employment/job-details.asp?id=4373&ref=ext| job details and application form]
 
  
−
== National Research Council of Canada: Research Officer, Statistical Semantics ==
 
  
−
* '''Employer:''' National Research Council of Canada
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
−
* '''Title:''' Research Officer
 
−
* '''Specialty:''' Statistical Semantics (2 positions)
 
−
* '''Deadline:''' Posted until filled
 
−
* '''Date Posted:''' January 20, 2009
 
−
* '''Link to website:''' [http://careers-carrieres.nrc-cnrc.gc.ca/careers/jobpost.nsf/EnglishAll/187241FAD78497FC85257540005E75CA Research Officer, Statistical Semantics (2 positions)]
 
  
−
The Institute for Information Technology at the National Research Council of Canada has openings for two Research Officers to work in the area of statistical semantics, a sub-field of statistical natural language processing. These two positions are full-time and continuing. They are based in Ottawa, Ontario. The successful candidates will perform original research that contributes to the Institute's focus on language processing, text mining, and machine translation. They will, in collaboration with other researchers and programmers, create prototypes of their work and publish their research results in highly-cited journals and conferences. The position offers the opportunity to collaborate with colleagues, university researchers, and industrial partners.
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
 +
* Title: Associate Research Scientist
 +
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
 +
* Location: Darmstadt
 +
* Deadline: March 8, 2017
 +
* Date posted: February 21, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]
  
−
The researchers will work in a results-driven environment and will have the opportunity to apply their research results to ongoing high profile projects, such as processing of textual medical records or performing machine translation.
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
  
−
== Postdoctoral and research engineer positions available at the Singapore Management University ==
+
'''Associate Research Scientist'''<br />
 +
'''(PostDoc- or PhD-level; for an initial term of two years)'''
  
−
The School of Information Systems at the Singapore Management University is seeking to fill a few postdoctoral and research engineer positions for the projects "Transfer Learning for Adaptive Relation Extraction" and "Mining Interaction Behaviors from Information Exchange Networks."  These are two-year projects supported by the Singapore Defense Science Organization, starting in April 2009.  
+
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.
  
−
The goal of the first project is to develop adaptive learning algorithms for relation extraction from free text. In real applications of relation extraction, there is often insufficient training data available for the target relations in the target domain, but labeled data from related domains or for related relation types can be borrowed. The research questions to be answered are therefore (1) how existing transfer learning algorithms can be applied in the particular context of relation extraction, (2) how human knowledge can be incorporated, and (2) what new transfer learning techniques are needed for adaptive relation extraction.
+
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 goal of the second project is to study characterization and measurement of interaction behaviors in information exchange networks based on user-generated interaction data.  We will focus on information exchange networks which involve actors sending information to one another.  Examples of such networks include email and blog networks. The research will focus on interaction behaviors that suggest actor roles in an information exchange network and may infer relationships between actors in the network.
+
* 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.  
  
−
The postdoctoral candidate must have completed all requirements for his/her PhD degree by the time of appointment. The research engineer candidate must have completed a good undergraduate or master degree in computer science or computer engineering. The ideal candidates are expected to have the following skills/qualifications:
+
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.
  
−
  - Knowledge and experience in machine learning, data mining and statistics/probabilities
+
UKP’s wide cooperation network both within its own research community
−
  - Strong programming skills
+
and with partners from research and industry provides an excellent
−
  - Proficiency in English
+
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.
  
−
For the first project, we also prefer candidates with
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
−
  - Knowledge and experience in natural language processing
+
Applications from women are particularly encouraged. All other things
−
  - Experience with information extraction, transfer learning and/or semi-supervised learning is a plus
+
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.
  
−
For the second project, we also prefer candidates with
+
==  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
  
−
  - Knowledge in social network analysis and web mining
+
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.
  
−
The salary for the postdoctoral position will be around 5,000 SGD per month. The salary for the research engineer position will be based on the candidate’s working experience and academic degree.
+
==  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
  
−
To apply for the positions, send your full CV with list of publications, names and contact information of two referees, a statement of research qualifications and interests, and two sample publications (if any) to the following principle investigators:
+
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.
  
−
  1. Transfer Learning for Adaptive Relation Extraction: Jing Jiang (jingjiang@smu.edu.sg).
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
−
  2. Mining Interaction Behaviors from Information Exchange Networks: Ee-Peng Lim (eplim@smu.edu.sg).
 
  
−
== Tenure Track Faculty Position: Assistant/Associate Professor in Human Computer Interaction, Montclair State University, NJ, USA ==
+
'''Essential criteria'''
  
−
Vacancy #: VF-22
+
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
−
Department: Computer Science
+
* 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.
−
The Department of Computer Science invites applications for a tenure track position in Human Computer Interaction (HCI) and Visualization. The Department’s 13 faculty members support the BS in Computer Science with an ABET CAC accredited track, the BS in Information Technology and the MS in Computer Science. The position requires a willingness to teach a variety of computer science and information technology courses at all levels to ethnically diverse students. The position entails the ability to work as a member of interdisciplinary teams as the Department develops and modifies computing undergraduate and graduate programs with a planned doctoral program in computational science. In addition, the successful candidate will develop and maintain an active research program with student involvement.
+
* Excellent programming skills.
−
+
* Knowledge of current status of research in specialist field.
−
Qualifications & Requirements: Candidates must have a Ph.D. in computer Science or a very closely related discipline. Candidates must have expertise in Human Computer Interaction with preference to candidates with experience in software engineering, interfaces, and visualization, and research in HCI. Candidates must have good communication skills. We are looking for candidates with experience in teaching undergraduate computing courses and in working as a member of a team. All faculty are expected to have an ongoing research program, to commit to quality teaching, to be involved in professional activities, and to pursue external funding to support their scholarship.
+
* 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.
−
Salary Range:            Salary and range is dependent on qualifications.
+
* Proven ability in effective and persuasive communication.
−
Anticipated Start Date:  September 1, 2009
+
* 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.  
  
−
Send letter and resume to (include vacancy # if above):
+
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.
−
Send hardcopy (no email documents) that includes C.V., at least three professional references, statement of research interests, teaching philosophy with experience, and professional goals to:
 
  
−
Search Committee — V- F22
+
'''More information'''
−
Department of Computer Science
 
−
Montclair State University
 
−
Montclair, NJ 07043
 
  
−
(include V number) and professional goals to:
+
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.
−
Search Committee — V- F22
 
−
Department of Computer Science
 
−
Montclair State University
 
−
Montclair, NJ 07043
 
  
−
Apply By: Screening begins immediately and continues until the position is filled.
+
==  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
  
−
Montclair State is a New Jersey State university. It is located 14 miles west of New York City.
+
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.
  
−
== Internship on Textual Entailment Applied to Statistical Machine Translation, Xerox Research Centre Europe, Grenoble - France ==
+
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. 
  
−
The main research lines within the Cross Language Technologies (CLT) area at XRCE are Statistical Machine Translation, Cross-Lingual Information Retrieval and Machine Learning Techniques for Cross-Lingual Applications. CLT is currently coordinating the European Project SMART (Statistical Multilingual Analysis for Retrieval and Translation) [http://www.smart-project.eu].
+
'''Skills'''
  
−
XRCE has received funding from the PASCAL-2 Network of Excellence [http://pascallin2.ecs.soton.ac.uk] for conducting, in partnership with Bar-Ilan University in Israel, a "Pump Priming" project on the topic of "Context Models for Textual Entailment and their Application to Statistical Machine Translation". One of the goals of the project is to investigate situations in which, while a translation system may not have enough knowledge to adequately translate a source text into a target text, it may be able to do so based on entailment rules learned from monolingual data.  
+
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.  
  
−
We are looking for preferably one (in this case the internship would be for 10 months ) or two interns (in this case each internship would last 5 months with the first starting at the beginning of 2009) to work on this topic under the supervision of XRCE researchers, and in collaboration with our partners. The focus of the work will be on the following topics:
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
−
* Integration of existing paraphrase and entailment resources into SMT settings, and assessment of their applicability in this domain;
+
'''Research Team'''
−
* Development (in collaboration with our partners) of novel models for assessing the validity of entailment rules in context and implementation of SMT-based modules that are able to exploit such rules;
 
−
* Methodology and measures for controlling the use of directional and bi-directional entailment rules in SMT;
 
−
* Use of entailment knowledge for evaluating the performance of SMT systems.
 
  
−
The ideal candidate will be a strong Master or Ph.D. student with background in statistical machine translation and/or statistical methods in NLP. The candidate will be fluent in C/C++ and/or Python. Some knowledge and practice of Machine Learning models and tools will be a plus, as will be some previous acquaintance with work on Textual Entailment.
+
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”.
  
−
Contact:  
+
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).
  
−
* Lucia Specia: lucia.specia@xrce.xerox.com
+
Deadline of applications: 13/03/2017
−
* Marc Dymetman: marc.dymetman@xrce.xerox.com
 
  
−
For more information: http://www.xrce.xerox.com/internships/LS-MD.TE-SMT_2009.2008.html
+
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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