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* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* Archived postings:
 
* Archived postings:
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** [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]
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** [[Employment opportunities posted 2016|2016]] - [[Employment opportunities posted 2015|2015]] - [[Employment opportunities posted 2014|2014]] - [[Employment opportunities posted 2013|2013]] - [[Employment opportunities posted 2012|2012]] - [[Employment opportunities posted 2011|2011]] - [[Employment opportunities posted 2010|2010]] - [[Employment opportunities posted 2009|2009]] - [[Employment opportunities posted 2008|2008]] - [[Employment opportunities posted 2007|2007]]
 
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== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==
  
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* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain
 +
* Title: PhD Scholarship
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* Specialty: Text Mining, Information Extraction, Music Information Retrieval
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* Location: Barcelona, Spain
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* Deadline: Until candidate is found
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* Date posted: June 10, 2017
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* Contact: [mailto:horacio.saggion@upf.edu]
  
  
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== Open PhD position on Textual Knowledge Resources (NLP / IR / ML) at Data and Web Science Group in Mannheim, Germany ==
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PhD position on data-driven methodologies for music knowledge extraction
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* Employer: The Data and Web Science Research Group, University of Mannheim, Germany
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In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.
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* Title: PhD Candidate (post-Masters)
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* Speciality: Natural Language Processing, Information Retrieval, Knowledge Bases
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Supervisors of the position: Xavier Serra and Horacio Saggion
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* Location: Mannheim, Germany
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Contact for application: Aurelio Ruiz (aurelio.ruiz@upf.edu)
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* Deadline: January 6, 2016
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* Date posted: November 20, 2015
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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.
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* Contact: queripidia-jobs(At)uni-mannheim(DoT)de
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The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .
  
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The Information Retrieval and Natural Language Processing Group at the University of Mannheim invite applications for
 
  
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'''ONE PHD STUDENT IN STATISTICAL NLP / IR / MACHINE LEARNING'''
 
  
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The student is expected to contribute to a project on Knowledge Consolidation and Organization for Query-specific Wikipedia Construction under the principal investigator Laura Dietz. The goal of the research project is to make information on the Web accessible in a Wikipedia-like form through a query-driven interaction paradigm. This research requires a combination of methods from information retrieval and automatic text understanding to provide the user with a synthesis of the information through summarization, sub-topic identification, and article organization.
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== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
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We are particularly interested in candidates with a background in one or several of the following areas:
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* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
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*   statistical text processing (e.g., automatic summarization, event extraction and ordering)
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* Title: Scientific System Developer
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*   machine learning
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* Specialty: Argument Mining, Machine Learning, Big Data Analysis
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*   knowledge base construction
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* Location: Darmstadt
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*   information retrieval
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* Deadline: May 31, 2017
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*   distributed large-scale processing
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* Date posted: May 3, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
  
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Applicants '''must have a Masters degree''' (or obtain it in the near future) in Computer Science, Natural Language Processing or Machine Learning with previous research experience in information retrieval and human language technologies is a plus. The successful candidate is expected work under limited supervision, and publish papers at top level conferences and journals and collaborate with other members of the research group.
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The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a
  
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Duration: initially one year (starting in Spring 2016) with possible extension of three years.
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'''Scientific System Developer'''<br>
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'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
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Salary range: according to German public scale TV-L 13 100% (full time, commensurate with experience and qualifications, ranging between 3200 and 4.600 Euro before taxes).
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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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'''Please submit your application per e-mail (queripidia-jobs(At)uni-mannheim(DoT)de) as a single PDF.''' This PDF should include a short research statement, CV, copy of university degrees, a list of publications and published software and contact details of three references. All applications sent before January 6, 2016 will receive full consideration. The position remains open until filled.
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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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The Data and Web Science Group is a joint lab of several professors covering diverse topics on managing, integrating and mining large-amounts of heterogeneous information within enterprise and open Web contexts. Further information about the group can be found at http://dws.informatik.uni-mannheim.de/ .
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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.
  
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The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.
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Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).  
  
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Please contact Laura Dietz (queripidia-jobs(At)uni-mannheim(DoT)de) for informal enquiries.
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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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Job posting at: http://bit.ly/1MWXjo1
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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
 +
We look forward to receiving your application!
  
  
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== Research position in Natural Language Processing/Text Mining, University of Manchester ==
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== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
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*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
 
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*Title: Postdoctoral Research Fellow
 
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*Speciality: Natural Language Processing, Text Mining
 
−
*Location: Manchester, UK
 
−
*Deadline: October 19, 2015
 
−
*Date posted: November 15, 2015
 
−
*Contact: sophia.ananiadou@manchester.ac.uk
 
  
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Applications are invited for a senior research fellow in Clinical Text Mining at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk) , School of Computer Science, University of Manchester.
+
* 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]
  
−
Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical/clinical Natural Language Processing/Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, Coling, etc., and in high quality journals; excellent Java skills; proven ability to develop research proposals independently.
+
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.  
  
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The objectives of this post are to conduct research into extracting complex information from the scientific literature and clinical case reports to facilitate the discovery of biomarkers using adaptive natural language processing and text mining methods.
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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)
−
* Duration of post: 1st November 2015 for 48 months
 
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* Salary: £38,511 to £42,067 per annum
 
  
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'''Research Environment '''
+
Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available.
  
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The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".
 
  
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The project involves collaboration with a large team working in a newly created interdisciplinary research centre (Manchester Molecular Pathology Innovation Centre, MMPathIC) funded by MRC/EPSRC, focusing on personalised medicine, improving diagnosis and treatment of inflammatory diseases, validating and evaluating biomarkers for improving patient outcomes.  
+
'''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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Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)
 
  
−
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=10521
+
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
  
−
== PhD Position: Deep Learning and Random Forest for Argumentation Mining ==
+
* Employer: University of Colorado Boulder
−
*Employer:University of Liège, Liège, Belgium
+
* Title: Postdoctoral Research Associate
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*Title: PhD Candidate
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* Specialty: Advanced Machine Learning
−
*Speciality: Natural Language Processing, Text Mining
+
* Location: Boulder, Colorado, United States
−
*Location: Liège, Belgium
+
* Deadline: Ongoing, desired start Summer/Fall 2017
−
*Deadline: November 23, 2015
+
* Date posted: March 31, 2017
−
*Date posted: October 8, 2015
+
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
−
*Contact: ashwin.ittoo@ulg.ac.be
 
  
−
The overall goal of this PhD project is to contribute to and advance the nascent field of AM. The selected candidate will have the opportunity to develop novel AM algorithms, which will then be applied to online reviews to evaluate their performance and to determine whether the presence of argumentative patterns are predictive of the helpfulness of online reviews.
+
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
 +
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
  
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The candidate will investigate the performance of two recent machine learning paradigms, Deep  Learning and Random Forests. The candidate will develop a sound understanding of these paradigms and propose novel Deep Learning and Radom Forest algorithms for AM. Other recent machine learning paradigms, in particular, minimally-supervised learning and distant supervision, will also be investigated. The proposed algorithms will be applied to online reviews in order to automatically detect argumentative patterns from the textual contents and determine whether the presence of these patterns influence the reviews’ helpfulness scores of
+
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.
  
−
Several corpora are already available for evaluation: product and service reviews from Amazon (books, movies), YELP and TripAdvisor. In addition, access to the Penn Discourse TreeBank (PDTB) is also available.
+
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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The selected candidate will be based at the HEC Management School, the University Liège, within the Operations department. Members of this department are engaged in research and teaching in “quantitative methods” (Operations Research, Machine Learning/Data Mining/Analytics, Enterprise Information Systems, Supply Chains and Logistics). The candidate will also collaborate with other international scholars in Japan, the Netherlands and France.
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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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The PhD project will span over a period of '''4 years''' and the candidate will be hired as a full-time PhD scholar. The '''gross salary will be around 2150 EUR per month (net: ~ 1800-1990 EUR)'''.
+
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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Interested candidates are required to send their '''CV (incl. publications if any)''' and a '''letter of motivation''' via e-mail to Prof. Ashwin Ittoo, '''ashwin.ittoo@ulg.ac.be by 23rd November 2015'''. Please clearly indicate ‘PhD application’ in the subject line. Only those candidates deemed most suitable for the research position will be contacted. The starting date is negotiable, but we would prefer candidates who could start soonest.  
 
  
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'''Required'''
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* Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)
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* 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)
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* Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record
  
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== Research Associate in Natural Language Processing and Machine Learning, National Centre for Text Mining, University of Manchester ==
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'''Desired'''
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*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
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* 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)
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*Title: Research Associate
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* Experience mentoring graduate and undergraduate students
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*Speciality: Natural Language Processing, Text Mining
 
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*Location: Manchester, UK
 
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*Deadline: October 3, 2015
 
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*Date posted: September 25, 2015
 
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*Contact: sophia.ananiadou@manchester.ac.uk
 
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Applications are invited for a researcher in NLP and machine learning at the National Centre for Text Mining (NaCTeM) (http://www.nactem.ac.uk), School of Computer Science, University of Manchester.
 
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The candidate will be joining a strong team with 10+ staff at NaCTeM carrying out cutting edge research in NLP, biomedical text mining and machine learning. The post is funded by the Medical Research Council and focuses on developing new algorithms for unsupervised and semi-supervised methods in information extraction, topic analysis, active learning, text classification using deep learning/neural networks to support the development of systematic reviews at the National Institute for Health and Care Excellence.
 
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Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing and Machine Learning; excellent knowledge in unsupervised NLP methods, deep learning, neural networks; excellent knowledge in topic analysis, clustering and classification; track record of high-quality papers in conferences such as ACL, EMNLP, etc., and excellent programming skills.
 
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* Duration of post: 1st November 2015 for 24 months
 
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* Salary: £30,434 to £37,394 per annum
 
  
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'''Research Environment '''
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'''Job Details'''
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* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.
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* Start date is negotiable, but anticipated for Summer/Fall 2017.
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* 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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The National Centre for Text Mining has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology management, text classification, text mining infrastructures and semantic search systems.
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'''How to apply''' <br/>
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NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.manchester.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research".
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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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NaCTeM is collaborating closely with the newly created Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST) in Japan (https://unit.aist.go.jp/airc//index.en.html), which focuses among others on data-knowledge integration, machine learning, natural language processing and text mining. The candidate will benefit from research stays and interactions with the team in Japan.
 
  
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Informal enquiries can be made to Prof. Sophia Ananiadou (sophia.ananiadou@manchester.ac.uk)
+
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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Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=103224.
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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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'''Questions''' <br/>
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Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
  
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==Research Positions at AIRC (Artificial Intelligence Research Center), Japan==
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== Researcher in Machine Learning and NLP, DFKI, Germany ==
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*Employer: Artificial Intelligence Research Center (AIRC), National Institute for Advanced Industrial Science and Technology (AIST)
 
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*Title: Post-doctoral research fellows
 
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*Speciality: Machine Learning, Deep Learning, Neuro-Computing, Natural Language Processing, Text Mining
 
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*Location: Tokyo, Japan
 
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*Deadline: October 16, 2015
 
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*Date posted: September 25, 2015
 
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*Contact: airc-recruit-ml@aist.go.jp
 
  
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Applications are invited for several positions in Artificial Intelligence at the Artificial Intelligence Research Center (AIRC) (https://unit.aist.go.jp/airc//index.en.html) under the auspices of the National Institute for Advanced Industrial Science and Technology (AIST) (http://www.aist.go.jp/index_en.html).
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* Employer: [http://www.dfki.de/ DFKI GmbH], Germany
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Successful candidates will join a strong and expanding team of 35+ full-time researchers carrying out cutting edge research in AI.  
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* Title: Researcher
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* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
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* Location: Saarbruecken
 +
* Deadline: March 31, 2017
 +
* Date posted: March 13, 2017
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* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]
  
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Research at AIRC includes Machine Learning, Deep Learning, Planning and Search, Text Mining, NLP, Pattern Recognition, Brain Inspired Computation, and infrastructures for AI．With strong research links to industrial partners, there is a particular emphasis on applications of AI technology to real world problems as well as research into theories and fundamental AI technologies. We work in close cooperation with partners in both the private and public sector to cover a broad range of AI applications, including:
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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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'''Key research responsibilities''' include:
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* machine and deep learning for natural language processing/machine translation
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* software development and integration
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* publication in top-tier conferences and journals
  
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* Artificial Intelligence for Human Life: Health-care, Smart city and Smart home, Innovative Retailing and Tourism, etc.
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'''General responsibilities''' include:
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* Artificial Intelligence for Manufacturing and Engineering: Intelligent Robots, Intelligent planning and control of manufacturing plants, etc.
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* engagement with industry partners and contract research
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* Artificial Intelligence for Big Sciences: AI applications in Bio-Medical Science and Material Science, Geology, Computational Sociology, etc.       
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* 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
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* Strong background and track record in machine learning, neural nets and deep learning
 +
* Strong background and track record in NLP and MT - Excellent programming skills
 +
* Excellent problem solving skills, independent and creative thinking
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* Excellent team working and communication skills
 +
* Excellent command of written and oral English
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* Command of German and other  languages not a requirement but helpful
  
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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).
  
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The advertised posts are funded by a project supported by NEDO (http://www.nedo.go.jp/english/index.html), which aims to establish a core research center for AI in Japan. Depending on the expertise and interest of the candidate, s/he will focus either on basic research or application related research of AI to real world problems. AIRC will carry out research in close cooperation with national or international research institutions such as Riken, CMU, Toyota Technology Institute in Chicago, the University of Manchester and DFKI.
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'''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 [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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Candidates should have a PhD in Computer Science with an emphasis on one of the following areas: Machine Learning, Deep Learning, Neuro-Computing, Planning and Search, Natural Language Processing, Text Mining, and Algorithms and Infrastructures for Big Data Analysis. Excellent programming skills and an excellent track-record of high-quality papers in top-tier conferences and journals would be a definite advantage.
+
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.
  
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'''Geographical environment:'''
 +
[http://www.saarbruecken.de/en Saarbrücken] is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.
  
−
We have three categories of post-doctoral research fellows. The duration of employment for all three categories is initially 24 months, with a possible extension of 36 months or longer, depending on performance. The starting date of employment will be 1st December 2015 at the earliest.
+
'''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.
  
−
* Category A: Post-Doctoral Research Fellow -  Salary 5,500,000 JPY to 7,000,000 JPY per annum
+
'''Application:'''
−
* Category B: Senior Post-Doctoral Research Fellow - Salary 7,000,000 JPY to 10,000,000 JPY per annum
+
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.
−
* Category C: Distinguished Research Fellow -  Salary 10,000,000 JPY per annum
 
  
  
−
'''Research Environment'''
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
  
 +
* 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]
  
−
AIST is one of the largest publicly funded research institutes in Japan and a single research institute under the Ministry of Economy, Trade and Industry (METI). AIRC is the newest research center within AIST, established in May, 2015.  As a core research center of AI in Japan, we have been establishing close cooperation with researchers at Japanese and international institutes, which include the University of Tokyo, Tokyo Institute of Technology, Riken, Osaka University, Tohoku University, National Institute of Informatics, Toyota Technology Institute in Chicago, CMU, University of Manchester and DFKI. 
+
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'''<br />
 +
'''(PostDoc- or PhD-level; for an initial term of two years)'''
  
−
AIRC is located in Odaiba, which is in one of the central districts of Tokyo, a bustling international city and the capital of Japan. Tokyo offers both the modern urban lifestyle of Japan as well as a rich Japanese heritage.  
+
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.
  
−
Interested candidates are invited to send, via electronic mail, the following items to the Director of Artificial Intelligence Research Center (AIST), Prof. Junichi Tsujii (airc-recruit-ml@aist.go.jp):
+
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.
  
−
* A cover letter that clearly indicates their main research interests
+
* 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.  
−
* Curriculum Vitae
+
* 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 contact details of 3 referees
 
−
* Copies of maximum of 3 publications that you have (co-)authored, and which are representative of your past research achievements. Each publication should be accompanied by a short summary that highlights its major contributions
 
−
* An agenda of future research goals. This should be no longer than one page, including figures
 
  
−
Informal enquiries can be made to airc-recruit-ml@aist.go.jp
+
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 [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.
  
−
NOTE: Please send your application to airc-recruit-ml@aist.go.jp directly via e-mail, and not by post. It is NOT necessary to follow the specific CV formats specified on the AIRC website.
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
−
+
Applications from women are particularly encouraged. All other things
 +
being equal, candidates with disabilities will be given preference.
 +
Please send the applications to:
 +
[mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 08.03.2017. The positions
 +
are open until filled. Later applications may be considered if the
 +
position is still open.
  
−
==Open Rank Tenure Line Position in Linguistics at Northwestern University==
+
== Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University ==
−
*Employer: Northwestern University
+
*Employer: Northwestern University, USA
−
*Title: Tenure-Line Professor (open rank)
+
*Title: Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University
 
*Speciality: Open area
 
*Speciality: Open area
 
*Location: Evanston, IL, USA
 
*Location: Evanston, IL, USA
−
*Deadline: December 1, 2015
+
*Deadline: April 1, 2017
−
*Date posted: August 31, 2015
+
*Date posted: February 17, 2017
 
*Contact: matt-goldrick@northwestern.edu
 
*Contact: matt-goldrick@northwestern.edu
  
−
The Department of Linguistics at Northwestern University seeks to fill a tenure-line position (open rank) with a start date of September 1, 2016. We are looking for candidates who pursue an integrated approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The candidate will join a vibrant interdisciplinary language sciences community including researchers from cognitive science, cognitive neuroscience, computer science, philosophy, psychology, and speech science.
+
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).
−
 
−
We seek exceptional candidates with forward-looking research programs that hold the promise of future external funding. Applicants that wish to be considered for appointment at the rank of Associate Professor or Professor are expected to have a record of excellence in research and teaching, success in obtaining external funding, and to have held both internal and external leadership roles.  
 
 
   
 
   
−
To receive fullest consideration, applications should arrive by December 1, 2015. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV (including contact information), statements of research and teaching interests, reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names of three references (with their contact information). Please visit http://www.linguistics.northwestern.edu/ for online application instructions.
+
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.
 
   
 
   
−
E-mail inquiries should be directed to Matt Goldrick, Chair (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.
+
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.
  
−
== One PHD / POSTDOC position in Text Analysis at the University of Mannheim ==
+
== Postdoctoral Research Position in Interpretable Machine Learning at Cardiff University, UK ==
−
* Employer: The Data and Web Science Research Group, University of Mannheim, Germany
+
*Employer: Cardiff University, UK
−
* Title: PhD or Postdoctoral Research Fellow
+
*Title: Research Associate in Artificial Intelligence / Machine Learning
−
* Topics: Natural Language Processing
+
*Speciality: Vector Space Models, Deep Learning, Interpretable Machine Learning, Symbolic Models
−
* Location: Mannheim, Germany
 
−
* Deadline: September 15, 2015
 
−
* Date Posted: August 20, 2015
 
−
* Contact: sfb884@informatik.uni-mannheim.de
 
−
 
 
−
The researcher is expected to contribute to the C4 project on “Measuring a common space and the dynamics of reform positions” within the DFG-funded Collaborative Research Centre (SFB) 884 “Political Economy of Reforms” (http://reforms.uni-mannheim.de) at the University of Mannheim. The topic of the PhD will focus on exploiting computational methods for analysing discourse phenomena like, e.g., uncertainty, vagueness and bias in political texts. This is a joint collaboration between the Natural Language Processing and Information Retrieval group (Prof. Simone Paolo Ponzetto) and the Chair of Artificial Intelligence (Prof. Heiner Stuckenschmidt), which will also involve close collaboration with project partners at the Department of Political Science (Prof. Dr. Nicole Rae Baerg, Prof. Dr. Thomas Gschwend), ranked as the best Political Science Department in Germany in different national and international university rankings. The student will be located at the Data and Web Science Group (DWS) of the University of Mannheim, one of leading centers for Data Science in Germany.
 
−
 
 
−
We are particularly interested in candidates with a background in one or several of the following areas:
 
−
 
 
−
* statistical semantics and discourse processing
 
−
* machine learning and natural language processing
 
−
* discourse analysis
 
−
* automated text-based scaling
 
−
 
 
−
Applicants should have a Masters degree (or obtain it in the near future) in Computer Science, Natural Language Processing, Machine Learning or Social Science and have previous experience in applying human language technology.
 
−
 
 
−
'''Duration:''' initially one year (starting in Fall 2015) with possible extension to 3-5 years.
 
−
'''Salary range:''' according to German public scale TV-L 13 100% (full time, ranging between 3200,- and 4.600,- Euro before taxes depending on qualification).
 
−
 
 
−
Applications can be made per e-mail (sfb884@informatik.uni-mannheim.de) and should include a short research statement, CV, copy of university degrees and transcripts and - if available - a copy of the master thesis, as well as list of publications and published software. Further information about the groups can be found at http://dws.informatik.uni-mannheim.de/. All documents should be e-mailed as a single PDF. All applications sent before '''September, 15 2015''' will receive full consideration. The positions remain open until filled.
 
−
 
 
−
The University of Mannheim is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.
 
−
 
 
−
Please contact Simone Paolo Ponzetto (simone(At)informatik(DoT)uni-mannheim(DoT)de) and Heiner Stuckenschmidt (heiner(At)informatik(DoT)uni-mannheim(DoT)de) for informal enquiries.
 
−
 
 
−
 
 
−
 
 
−
 
 
−
 
 
−
== Postdoctoral Fellow in NLP for EEG Analysis at Temple University ==
 
−
* Employer: The Neural Engineering Data Consortium, College of Engineering, Temple University
 
−
* Title: Postdoctoral Research Fellow
 
−
* Topics: Natural Language Processing, Machine Learning, Big Data, EEG Analysis
 
−
* Location: Philadelphia, PA
 
−
* Deadline: Open until filled
 
−
* Date Posted: August 12, 2015
 
−
* Contact: Joseph Picone (joseph.picone@gmail.com)
 
−
 
 
−
'''Research focus''': The Neural Engineering Data Consortium (NEDC) at Temple University invites applications for a Postdoctoral Fellow position in the area of automated EEG analysis. The Postdoctoral Fellow will contribute to a project that enables comparative research by automatically uncovering clinical knowledge from a vast BigData archive of clinical EEG signals and EEG reports collected over the past 14 years at Temple University Hospital (see www.isip.piconepress.com/projects/tuh_eeg for more information). We are developing a proof-of-concept based on the discovery of patient cohorts and provide an annotated BigData archive as well as the software that enabled the annotations and the generation of the patient cohort retrieval system. The candidate will be involved in overseeing the generation of labeled data for machine learning training, developing algorithms to automatically uncover and model structure based on deep
 
−
learning principles, implementing an active learning approach that minimizes the amount of labeled data needed and supervising research to automatically extract medical concepts from EEG reports. A large portion of the project focuses in extraction of information from unstructured text, and hence, expertise in natural language processing is important.
 
−
 
 
−
'''Supervisor''': Iyad Obeid, PhD and Joseph Picone, PhD
 
−
 
 
−
'''Required skills''': The candidate’s primary expertise will be in natural language processing and/or computational linguistics. Proficiency in machine learning and big data techniques is highly desirable. Software engineering experience is also desired.
 
−
 
 
−
'''Education''': A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required.
 
−
 
 
−
'''Length of appointment''': This position is for three years.
 
−
 
 
−
'''Available''': October 1, 2015.
 
−
 
 
−
'''Compensation''': $42,000/year (NIH standard scale applies).
 
−
 
 
−
'''To apply''': Send a CV and cover letter to joseph.picone@gmail.com (see http://www.isip.piconepress.com/images/memorabilia/temple/20150811_postdoc/postdoc_announcement_v00.pdf for more details)
 
−
 
 
−
 
 
−
== Postdoctoral Fellow in Sentiment Analysis at McMaster University ==
 
−
* Employer: Department of Linguistics, Department of Computing and Software, McMaster University
 
−
* Title: Postdoctoral Research Fellow
 
−
* Topics: Sentiment Analysis, Natural Language Processing
 
−
* Location: Hamilton, ON, Canada
 
−
* Deadline: Open until filled
 
−
* Date Posted: July 24, 2015
 
−
* Contact: Victor Kuperman (vickup@mcmaster.ca)
 
−
 
 
−
'''Research focus''': Successful applicants will be working closely with a vibrant cross-faculty team of linguists, psychologists and computer scientists. The selected candidate will contribute to a research program that explores individual and group (gender, age) variability in perception and regulation of emotion. Primary responsibilities will include investigating new algorithmic techniques for identifying fine-grained sentiment on textual data, and semi-structured data, including social media. Equally important to the project is the development of lexical-semantic tools allowing big data analyses of text corpora for the purposes of text classification, topic modeling, development of semantic networks, and estimation of semantic similarity.
 
−
 
 
−
'''Supervisor''': Victor Kuperman, PhD, Fei Chiang, PhD
 
−
 
 
−
'''Required skills''': The candidate’s primary expertise will be in natural language processing, sentiment analysis, and/or computational linguistics. Proficiency in machine learning techniques is highly desirable.
 
−
 
 
−
'''Education''': A Ph.D. in computer science, computational linguistics, artificial intelligence or similar disciplines is required.
 
−
 
 
−
'''Length of appointment''': This position is for two years.
 
−
 
 
−
'''Available''': August 1st, 2015.
 
−
 
 
−
'''Compensation''': $50,000/year.
 
−
 
 
−
'''To apply''': see application procedure at http://www.cas.mcmaster.ca/~fchiang/misc/postdoc.pdf
 
−
 
 
−
 
 
−
 
 
−
== Postdoctoral Fellow in Natural Language Processing at Brigham and Women's Hospital / Harvard Medical School ==
 
−
* Employer: Brigham and Women's Hospital / Harvard Medical School
 
−
* Title: Postdoctoral Research Fellow
 
−
* Topics: Natural Language Processing
 
−
* Location: Boston, MA
 
−
* Deadline: Open until filled
 
−
* Date Posted: July 11, 2015
 
−
* Contact: Alexander Turchin (aturchin@bwh.harvard.edu)
 
−
 
 
−
'''Research focus''': the Fellow will work in a multi-disciplinary team of artificial intelligence scientists, informaticians, biostatisticians, and clinicians on projects involving development of open-source natural language processing framework software and high-dimensional predictive models that utilize a combination of artificial intelligence and natural language processing of multiple narrative document streams.
 
−
 
 
−
'''Supervisor''': Alexander Turchin, MD, MS, FACMI
 
−
 
 
−
'''Required skills''': strong programming and system development skills; ability to design and conduct effective research studies; strong analytical, scientific writing, presentation and communication skills. Experience in programming in Perl and .NET and experience with natural language processing and medical terminologies / ontologies is a strong plus.
 
−
 
 
−
'''Education''': PhD in computer science, biomedical informatics, linguistics, or related discipline, MD or an equivalent degree.
 
−
 
 
−
'''Length of appointment''': This position is for one year with second and third year reappointment dependent on satisfactory performance and availability of funding.
 
−
 
 
−
'''Available''': August 1st, 2015.
 
−
 
 
−
'''Compensation''': according to NIH (NRSA) stipend levels.
 
−
 
 
−
'''To apply''': send cover letter and CV to Dr. Alexander Turchin at aturchin@bwh.harvard.edu.
 
−
 
 
−
 
 
−
== Data Scientist - Unstructured Data at Civis Analytics ==
 
−
* Employer: [https://civisanalytics.com Civis Analytics]
 
−
* Title: Data Scientist - Unstructured Data
 
−
* Topics: Natural Language Processing,  Machine Learning, Deep Learning, Big Data Analytics, Computer Vision, Speech Processing, Algorithm Development
 
−
* Location: Chicago, IL
 
−
* Deadline: Open until filled
 
−
* Date Posted: June 23, 2015
 
−
* Apply Online: [https://civisanalytics.com/careers civisanalytics.com/careers]
 
−
* Questions: apply@civisanalytics.com
 
−
 
 
−
 
 
−
'''Who We Are'''
 
−
 
 
−
Civis Analytics is building a data-driven world. We create technologies that empower organizations to unlock the truth hiding in their own data—transforming them into smart organizations that are ready to thrive.
 
−
 
 
−
While our history is rooted in political campaign targeting, we’re now partnering with intelligent organizations in healthcare, media, education, and a range of other domains. We’re also building cloud-based products to do data science better.
 
−
 
 
−
We're solving the world's biggest problems with big data. Through research, experimentation, and iteration, we’re transforming how organizations do analytics. Our clients range in scale and focus from local to international, all empowered by our individual-level, data-driven approach.
 
−
 
 
−
Our incredible team of engineers, statisticians, researchers, and solution seekers come from all over the world with diverse backgrounds in Fortune 500 companies, international non-profits, Ivy League academia, and even actual rocket science.
 
−
 
 
−
'''Why should you join our team?'''
 
−
 
 
−
We are already hard at work on solving the world’s toughest problems with Big Data – working with organizations to analyze and understand their individual level data to improve outcomes and implement organizational change. We use cutting edge data science techniques, and we want to continue be on the forefront of innovation in our field.
 
−
 
 
−
We are ''smart'', ''fun'', and ''a little bit weird''. ''Does this sound like you?''
 
−
 
 
−
'''Position Overview'''
 
−
 
 
−
The Research and Development team is responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company. Our diverse work includes predictive analytics, algorithm development, experimental design, visualization, and survey research.
 
−
 
 
−
As a Data Scientist on our Chicago-based Research and Development team, you will work closely and collaboratively with analysts and engineers to develop and operationalize the techniques that quantify and solve big, meaningful problems. Our team dives deeply into big problems and works in a variety of areas. With a specialization in unstructured data, this Data Scientist role will apply techniques from fields such as machine learning, applied statistics, natural language processing, computer vision, and speech processing to the growing unstructured datasets being collected at Civis. Because the majority of the world’s information is unstructured, being able to leverage these diverse and voluminous data sources adds tremendous value to Civis products and research. In this role, you will be a critical voice shaping both how unstructured data informs existing Civis products and services, and how it leads to the development of entirely new ways of serving our clients, novel to the industry as a whole.
 
−
 
 
−
We are looking for individuals from a diversity of backgrounds with demonstrated quantitative and problem-solving skills. We value creativity, hard work, and on-the-job-excellence and offer competitive compensation and benefits packages. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
'''MINIMUM QUALIFICATIONS'''
 
−
 
 
−
* Bachelor’s degree in a quantitative field, such as computer science, statistics, machine learning, or electrical engineering
 
−
* Knowledge of and practical experience in applying the methodology of one or more unstructured data analysis fields, such as natural language processing, speech processing, or computer vision
 
−
* Familiarity with statistical packages such as R, Stata, or in the Python scientific stack (NumPy, SciPy, scikit-learn, pandas)
 
−
* Experience with common toolkits for unstructured data analysis, such as Theano, Torch, open-cv, the Stanford NLP tools, HTK, and Kaldi
 
−
* Experience with SQL databases
 
−
* Strong programming skills
 
−
* Experience identifying and correcting for problems in imperfect data
 
−
* An ability and eagerness to constantly learn and teach others
 
−
 
 
−
'''PREFERRED QUALIFICATIONS'''
 
−
 
 
−
* Master’s degree in a quantitative field such as computer science, statistics, machine learning, or electrical engineering
 
−
* Significant work experience in applying the methodology of one or more unstructured data analysis fields
 
−
* High proficiency in programming with Python, Go, Java, Lua, C, or other languages used for high-performance statistical computing
 
−
* Familiarity with architectures for scaling statistical computing to big data applications, such as Hadoop and Spark
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Apply online at: [https://civisanalytics.com/careers civisanalytics.com/careers]
 
−
 
 
−
== Postdoctoral Fellow in NLP at University of Pennsylvania ==
 
−
* Employer: Dept. of Computer and Information Science, University of Pennsylvania
 
−
* Title: Postdoctoral Researcher
 
−
* Topics: Natural Language Processing, Unsupervised Learning
 
−
* Location: Philadelphia, PA
 
−
* Deadline: Open until filled
 
−
* Date Posted: June 19, 2015
 
−
* Contact: Mitch Marcus (mitch@cis.upenn.edu)
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
Applications are invited for a postdoctoral fellow research associate position in the Department of Computer and Information Science at the University of Pennsylvania.  This is a full time position for 24 months, starting immediately.
 
−
 
 
−
The main aim of this project is to develop new unsupervised algorithms to extract several levels of linguistic structure including morphology, part of speech (POS) tags, and noun phrases from unannotated corpora.  The project will exploit many different descriptive properties and constraints of language, all of which are close to universal in applicability. Such so-called universals have been developed across a wide range of often conflicting theoretical frameworks by both theoretical and descriptive linguists over many years, and we intend to shamelessly exploit them all.
 
−
 
 
−
The candidate will work under the supervision of Profs. Mitch Marcus and Lyle Ungar in Computer and Information Science and Prof. Charles Yang in Linguistics.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
The candidate should have a very strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science with a good publication record.  Experience in machine learning, good programming skills, and a good knowledge of modern linguistics are required. 
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Please email your CV and the names and contact information of three or more references to Mitch Marcus at the email provided above.
 
−
 
 
−
 
 
−
== Postdoctoral Fellow in Machine Learning/Computational Linguistics for Child Language Acquisition ==
 
−
* Employer: University of Liverpool
 
−
* Title: Post-doctoral fellow
 
−
* Topics: machine learning, computational linguistics, corpus linguistics, algorithm development, deep learning, speech processing
 
−
* Deadline: 28th August 2015
 
−
* Date Posted: 2nd June 2015
 
−
* Apply: http://www.liv.ac.uk/working/jobvacancies/currentvacancies/research/r-588063/
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
We are recruiting for post-doctoral fellow to work on the application of machine learning/computational linguistic techniques to child language acquisition.
 
−
 
 
−
You should have a PhD in Computer Science/Engineering/Linguistics/Psychology and have experience with machine learning algorithms applied to language data and have published your work in conference proceedings or journals. Experience with auditory speech processing, deep learning, cloud computing, and GPU programming is desirable. The post is available for 2 years.
 
−
 
 
−
The computational community has developed a wealth of algorithms that can automatically discover linguistic units and dependencies between these units and these algorithms have been applied to language parsing and generation. In contrast, child language researchers often study child language using human coding of detailed linguistic information. The goal of this project is to develop a bridge between these two approaches. Machine learning techniques would give child language researchers ways to pull out relevant utterances that could be subject to greater processing. Child language analyses could be compiled into test sets that could be used to evaluate machine learning algorithms. In this post, you will develop machine learning algorithms for child language and also develop a web site that will enhance the ability of machine learning researchers and child language researcher to share data and algorithms.  The research topics and approaches are open to negotiation.  Children have some of the most advance language learning algorithms and understanding how they learn language could lead to new insights for computational approaches to language.
 
−
 
 
−
This post offers the opportunity to join a thriving research group at the University of Liverpool and become a member of the new ESRC International Centre for Language and Communicative Development, a multi-million pound collaboration between the Universities of Liverpool, Manchester and Lancaster.
 
−
 
 
−
More information is available here:
 
−
https://sites.google.com/site/sentenceproductionmodel/news
 
−
 
 
−
==Postdoctoral Fellow and Software Engineer postions in biomedical natural language processing, machine learning and biomedical informatics==
 
−
* Employer: UMass Medical School Worcester
 
−
* Title: Post-doctoral fellow or Software Engineer
 
−
* Topics: Biomedical natural language processing, machine learning, bioinformatics, algorithm development, big data analytics
 
−
* Deadline: until filled
 
−
* Date Posted: 24 May 2015
 
−
* apply by contacting elaine.freund@umassmed.edu
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
We are recruiting for multiple positions at levels from Post Doctoral Fellow to Software Engineer to participate research and software development in biomedical natural language processing (NLP) and biomedical informatics.  The group’s research (http://www.bio-nlp.org/index.php/projects) involves developing algorithms and tools for gathering, analyzing and interpreting heterogeneous data from multiple sources both clinically and research related. Recruits will lead development efforts in web service tools and search engines that: retrieve and summarize big data in biomedical domain, automatically extracting information from pdf files and extracting text from images, integrate novel biomedical text mining algorithms into the web tools and search engines to enable intelligent semantic search, and mining electronic health record data for pharmacovigilance.
 
−
 
 
−
If you are highly motivated and passionate about research in big data processing or software engineering or have in-depth knowledge and hands on implementation experience with web service tools and are interested in learning more about us, please contact elaine.freund@umassmed.edu with your resume or CV and a cover letter.
 
−
 
 
−
General Summary of Postdoc Fellow Position: PhD in Computer Science, computational linguistics or Biomedical Informatics with expertise in natural language processing, machine learning or information retrieval with excellent writing and communication skills and ability to work with the research team. 
 
−
 
 
−
General Summary of Software Engineer Position:
 
−
Under the direction of the Faculty or designee, the Software Engineer I assists with the design, development, implementation and integration of web service tools, search engines, utilities, applications and enhancements in a complex medical/academic research computing environment.
 
−
 
 
−
==Research Scientist in natural language processing, machine learning, knowledge discovery, data analytics at IBM Research-Almaden==
 
−
* Employer: IBM Research
 
−
* Title: Research Scientist
 
−
* Topics: Nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics
 
−
* Location: San Jose, California, USA
 
−
* Deadline: 1 June 2015
 
−
* Date Posted: 6 May 2015
 
−
* Online application: https://jobs3.netmedia1.com/cp/faces/job_summary?job_id=RES-0751127
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
IBM Research - Almaden is looking for researchers to join the Natural Language Processing (NLP), Entity Resolution and Discovery (NERD) Department. Our research focuses include high-value content creation from variety of public and third-party data sources, scalable and usable analytics tools for individual stages in analyzing such data sources, such as text analytics, entity resolution, large-scale machine learning, techniques and methods for scalable and flexible indexing and querying support over enriched content, and consumable interfaces for accessing such data sources, including natural language interfaces. An example project is SystemT (http://ibm.co/1Cdm1Mj).
 
−
 
 
−
We are currently looking for a Research Staff Member to conduct research with large scale real-world heterogeneous data in the area of advanced analytics, such as nature language processing, information integration, entity resolution, machine learning, knowledge discovery, and data analytics. This role generates highly novel ideas, both theoretical and experimental, in a specific engineering or scientific discipline and invents and designs complex products and processes. This position may be involved in engineering these ideas to an advanced state of feasibility by evaluating ideas and plans and participating in their design and development. The full cycle of innovation to delivery is typically a multiple-year effort.
 
−
 
 
−
The candidate is also responsible for internally and externally disseminating the results of such activities through publications, patent disclosures, seminar participation, technical documentation, etc. The candidate represents IBM at professional conferences, in professional societies and universities and functions as an internal consultant in the areas of professional expertise.
 
−
 
 
−
'''Required'''
 
−
 
 
−
* Master's Degree
 
−
* At least 1 year experience in developing advances in Computer Science disciplines
 
−
* At least 1 year experience in performing Scientific Research
 
−
* English: Intermediate
 
−
 
 
−
'''Preferred'''
 
−
 
 
−
* Doctorate Degree in Information Technology
 
−
* At least 3 years experience in developing advances in Computer Science disciplines
 
−
* At least 3 years experience in performing Scientific Research
 
−
* English : Fluent
 
−
 
 
−
'''Additional Information'''
 
−
 
 
−
The World is Our Laboratory: No matter where discovery takes place, IBM researchers push the boundaries of science, technology and business to make the world work better. IBM Research is a global community of forward-thinkers working towards a common goal: progress.
 
−
 
−
IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
 
−
 
 
−
 
 
−
==PhD position in statistical language modelling==
 
−
* Employer: Cardiff University
 
−
* Title: PhD scholarship
 
−
* Topics: Statistical language modelling, relation extraction, social media
 
−
* Location: Cardiff, UK
 
−
* Deadline: 1 June 2015
 
−
* Date Posted: 7 April 2015
 
−
* Online application: http://courses.cardiff.ac.uk/funding/R2497.html
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
Applications are invited for a PhD Scholarship at the Cardiff School of Computer Science & Informatics in the area of statistical language modelling. Specifically, the aim of the project will be to develop methods for modelling the meaning of natural language terms, based on data from social media and other web sources. For example, by analysing the tags associated with Flickr photos, the developed methods will be able to learn that a church is a kind of building, that churches tend to be larger than typical buildings and that chapels are similar to churches. The results of this project will be used to improve methods from artificial intelligence for commonsense reasoning, and will among others enable more intelligent web search engines.
 
−
 
 
−
'''Funding and eligibility'''
 
−
 
 
−
This studentship consists of full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£14,057 p.a. for 2015/16, updated each year). This studentship is open to students of any nationality. Students classified as international for fee purposes have to self-fund the difference between home and international fees.
 
−
 
 
−
Candidates should:
 
−
 
 
−
* either have (or expect to have by Autumn 2015) a good honours degree in a relevant discipline (minimum 2:1);
 
−
* or have a masters degree with distinction in the research dissertation in a relevant discipline;
 
−
* or have professional qualifications deemed by Cardiff University to be equivalent to the above;
 
−
* or be over 25 and have relevant work experience in a position of responsibility.
 
−
 
 
−
The methods will rely heavily on methods from statistics and linear algebra, hence a strong background in mathematics will be required, in addition to excellent programming skills. A strong mathematical background and excellent programming skills will also be required.
 
−
 
 
−
Applicants are particularly welcomed from candidates with a background in computer science.
 
−
 
 
−
If your first language is not English you must provide evidence of competence in English. Our standard requirement is an overall IELTS result of at least 6.5, with a minimum of 6.5 in writing, and a minimum of 6.0 in speaking, listening and reading.
 
−
 
 
−
'''Further information'''
 
−
 
 
−
For further information and instructions on how to apply, please see http://courses.cardiff.ac.uk/funding/R2497.html
 
−
 
 
−
==Postdoctoral Researcher in NLP at U.S. Army Research Lab==
 
−
* Employer: U.S. Army Research Lab, Adelphi Laboratory Center
 
−
* Title: Postdoctoral Researcher
 
−
* Topics: Natural Language Processing
 
−
* Location: Adelphi, MD, USA
 
−
* Deadline: Open until filled
 
−
* Date Posted: March 17, 2015
 
−
* Contact: Dr. Stephen Tratz (stephen.c.tratz.civ@mail.mil)
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The Multilingual Computing Branch (MLCB) at the U.S. Army Research Laboratory's Adelphi Laboratory Center, located in the Washington, D.C. metro area, is seeking to hire new post-doctoral fellows. MLCB has several ongoing efforts in computational linguistics/natural language processing, including active projects in machine translation, human-robot communication, and social media analysis. The branch is also pursuing new interdisciplinary initiatives to address the language processing challenges in cyber-security and video analytics.
 
−
 
 
−
Candidates should have substantial research experience in machine learning methods (e.g., deep neural networks) as applied to emerging areas involving computational linguistics.  Areas of interest include:  text/video analytics, computational social science, machine translation, domain adaptation, data selection, low-resource language processing, morphologically complex languages, knowledge representation and reasoning, spoken language interfaces and dialogue, and multimedia processing.
 
−
 
 
−
The lab encourages external collaboration and maintains multiple partnerships with universities and research institutions, which enable faculty and student exchanges as well as joint research and publishing (http://www.arl.army.mil/www/default.cfm?page=93). ARL’s new open campus initiative is attracting national and international partners from academia and industry to work with ARL scientists and engineers in areas of common research interest (see http://www.arl.army.mil/www/default.cfm?page=2357), and ARL researchers have begun releasing open source code via GitHub (see http://www.army.mil/article/141734/Army_cyber_defenders_open_source_code_in_new_GitHub_project/).  ARL facilities include multiple high-end supercomputing clusters with over 10,000 cores and capable of at least 350 TFlops.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
* Ph.D. or equivalent research experience in computer science, statistics, mathematics, or related field
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
If interested, please email your CV and the names and contact information of three or more references to Dr. Stephen Tratz at the email provided above.
 
−
 
 
−
==Postdoctoral Researcher in NLG for Narrative==
 
−
* Employer: Liquid Narrative Group, North Carolina State University
 
−
* Title: Postdoctoral Research Scholar
 
−
* Topics: Natural Language Generation, Narrative Generation, Knowledge Representation, AI Planning
 
−
* Location: Raleigh NC, USA
 
−
* Deadline: Open Until Filled
 
−
* Date Posted: March 10, 2015
 
−
* Online Application: http://jobs.ncsu.edu/postings/40524
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The Liquid Narrative group at North Carolina State University is seeking a postdoctoral researcher to collaborate on a large-scale narrative generation project. The goal of this project is to build computational tools for the use of narrative in sense-making tasks. Research thrusts include the creation of formalisms for representing story and discourse knowledge and the development of narrative generation algorithms able to create multiple narrative discourses from a given story, adapt these discourses to an audience, and elicit different effects such as surprise or suspense. This project aims at creating a large-scale narrative-generation system that can extract story data from various sources (e.g., video game logs) and create narratives in and across several media such as text, animated movies or maps.
 
−
 
 
−
The postdoctoral researcher will contribute to the design and development of narrative generation and summarization technologies, focusing on the microplanning aspect of text generation. In particular, he or she will extend an existing narrative discourse generation prototype that outputs basic sentences using the SimpleNLG library. Our aim is to update this architecture by integrating an NLG system such as FUF/Surge, KPML or RealPro. To improve the quality of the generated text, the postdoctoral researcher will work on topics such as: aggregation, generation of referring expressions, discourse markers insertion, lexical choice and/or other aspects of realization that are specific to narrative as a genre.
 
−
 
 
−
He/she may also participate in research efforts on the automated generation of multimedia presentations involving text, video and maps. He/she is expected to collaborate in performing scientific evaluations of the systems, and in writing academic research papers.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
The applicant must hold a PhD degree, preferably in the area of computational linguistics or natural language generation. He/she should have:
 
−
* Experience with developing NLG systems
 
−
* Excellent software-design and problem-solving skills
 
−
* Good programming skills
 
−
* Excellent written and oral communication skills
 
−
 
 
−
Experience in the following areas would be a plus:
 
−
* Automated discourse planning technologies
 
−
* Dialogue generation
 
−
 
 
−
'''Position details'''
 
−
 
 
−
This is a full-time position.
 
−
Expected start date is April 1, 2015 and the initial funding for the position runs through December 31, 2015.  The position may be extendable depending on availability of funds.
 
−
 
 
−
Interested candidates should view the official Human Resources posting and submit applications through the NC State University HR web page at http://jobs.ncsu.edu/postings/40524
 
−
 
 
−
NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, age, sexual orientation, genetic information, status as an individual with a disability, or status as a protected veteran.  Individuals with disabilities requiring disability-related accommodations in the application and interview process, please call 919-515-3148.
 
−
 
 
−
 
 
−
==PhD-level Researchers in Language Technology or Computational Linguistics==
 
−
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)
 
−
* Title: PhD-level Researchers in Language Technology or Computational Linguistics
 
−
* Topics: Natural Language Processing, Summarization, Opinion Mining
 
−
* Location: Darmstadt (Germany)
 
−
* Deadline: open until the position is filled
 
−
* Date Posted: March 4, 2015
 
−
* Contact: Prof. Iryna Gurevych apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The newly established Research Training Group „[http://www.aiphes.tu-darmstadt.de Adaptive Information Processing of Heterogeneous Content]“ (AIPHES) at the Technische Universität Darmstadt and at the Ruprecht-Karls-University Heidelberg is filling several positions for three years, starting as soon as possible:
 
−
 
 
−
PhD-level Researchers in Language Technology or Computational Linguistics
 
−
 
 
−
The positions provide the opportunity to obtain a doctoral degree with an emphasis within one of the following guiding themes:
 
−
 
 
−
* A3: Opinion and Sentiment - extrapropositional aspects of discourse (Univ. of Heidelberg)
 
−
* B1: Structured summaries of complex contents (TU Darmstadt)
 
−
* B2: Content selection based on linked lexical resources (TU Darmstadt)
 
−
* D1: Multi-level models of information quality in online scenarios (TU Darmstadt)
 
−
* D2: Manual and Automatic Quality Assessment of Summaries from Heterogeneous Sources (TU Darmstadt)
 
−
The funding follows the guidelines of the DFG, and the positions are paid according to the E13 public service pay scale.
 
−
 
 
−
The goal of AIPHES is to conduct innovative research on multi-document summarization in a cross-disciplinary context. To that end, methods in computational linguistics, natural language processing, machine learning, network analysis, and automated quality assessment will be developed. AIPHES will investigate a novel summarization scenario for information preparation from heterogeneous sources. There will be close interaction with end users who prepare textual documents in an online editorial office, and who should therefore profit from the results of AIPHES. In-depth knowledge in one of the above areas is desirable but not a prerequisite.
 
−
 
 
−
Participating research groups at the Technische Universität Darmstadt are Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge Processing (Prof. Gurevych, Dr. Eckle-Kohler), Algorithmics (Prof. Weihe), Language Technology (Prof. Biemann), Multimedia Communications (Dr. Rensing). Participants at the Ruprecht-Karls-University Heidelberg are the Institute for Computational Linguistics (Prof. Frank) and the Natural Language Processing Group (Prof. Strube) of Heidelberg Institute for Theoretical Studies (HITS). Cooperating partners are the Institute for Communication and Media of the University of Applied Sciences Darmstadt and other partners in the area of online media.
 
−
 
 
−
AIPHES will emphasize close contact between students and their advisors, have regular joint meetings, a co-supervision by professors and younger scientists in the research groups, and an intensive exchange as part of the research and qualification program. The training group has the goal of publishing its results at leading scientific conferences and will actively support its doctoral researchers in this endeavor. The software that will be developed in the course of AIPHES should be put under the open source Apache Software License 2.0 if possible. Moreover, the research papers and datasets should be published with open access models.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
We are looking for exceptionally qualified candidates with a degree in Computer Science, Computational Linguistics, or a related study program. We expect ability to work independently, personal commitment, team and communication abilities, as well as the willingness to cooperate in a multi-disciplinary team. Desirable is experience in scientific work. Applicants should be able to work with German-language texts, and, if necessary, to acquire German language skills during the training program. We specifically invite applications of women. Among those equally qualified, handicapped applicants will receive preferential consideration. International applications are particularly encouraged.
 
−
 
 
−
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web” emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge. The Institute for Computational Linguistics (ICL) of the Ruprecht-Karls-University Heidelberg is one of the large centers for computational linguistics both in Germany and internationally. The ICL and the NLP department of the HITS jointly run the graduate program „Semantic Processing“ with an integrated research training group “Coherence in language processing: Semantics beyond the sentence”, which has a close connection to the topics in computational linguistics of AIPHES.
 
−
 
 
−
Applications should include
 
−
 
 
−
* a motivational letter that refers to one of the above listed guiding themes,
 
−
* a CV with information about the applicant’s scientific work,
 
−
* certifications of study and work experience,
 
−
* as well as a thesis or other publications in electronic form.
 
−
They should be submitted until March 23th, 2015 to the spokesperson of the research training group, Prof. Dr. Iryna Gurevych (Fachbereich Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address apply-for-aiphes(a-t)ukp.informatik.tu-darmstadt.de. The interviews may start any time. The positions are open until filled.
 
−
 
 
−
 
 
−
==Research staff position in Natural Language Processing==
 
−
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)
 
−
* Title: Research staff position in Natural Language Processing
 
−
* Topics: Natural Language Processing, Question Answering
 
−
* Location: Darmstadt (Germany)
 
−
* Deadline: open until the position is filled
 
−
* Date Posted: March 4, 2015
 
−
* Contact: Nicolai Erbs erbs@ukp.informatik.tu-darmstadt.de
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The [https://www.ukp.tu-darmstadt.de Ubiquitous Knowledge Processing Lab] (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a research staff position (TV-TU E13 German payscale) with a focus on question answering and summarization of social media content. This DFG-funded basic [https://www.ukp.tu-darmstadt.de/research/current-projects/qa-eduinf research project] conducts research integrating semantic text analysis, such as semantic role labeling (SRL), into higher-level applications in information access to improve their overall results (Principal Investigator: Prof. Dr. Iryna Gurevych). Thereby, we pay special attention to graph-based techniques.
 
−
 
 
−
The selected candidate will work with a large corpus from a social question-answer platform on the Web. He/she will be expected to identify interesting research problems, research ways of utilizing semantic role labeling in novel NLP tasks, and develop means and resources to evaluate the results. The newly established Research Training Group “[http://www.aiphes.tu-darmstadt.de Adaptive Information Processing of Heterogeneous Content]” (AIPHES) funded by the DFG [3] provides an excellent research environment for this kind of work. The funding is available for the duration of at least two years with an option for extension.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
We ask for applications from applicants in Computer Science or Computational Linguistics, preferably with completed PhD and research publications. Experience in Question Answering or a related field like summarization or information retrieval is a definite advantage. Excellent graduates of these disciplines willing to work towards a PhD are also encouraged to apply. Ideally, the candidates should have strong research skills as well as demonstrable experience in designing and implementing complex natural language processing (NLP) applications in Java and/or with graph-based algorithms. A very good command of German is a definite plus, since the target corpus is in the German language. Excellent communication skills in English and the ability to work in a team are required.
 
−
 
 
−
Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees. Applications from women are particularly encouraged.  All other things being equal, candidates with disabilities will be given preference. Please send the application to: erbs@ukp.informatik.tu-darmstadt.de by 23.03.2015. The position is open until filled.
 
−
 
 
−
 
 
−
==PhD-position in NLP/Text Mining==
 
−
* Employer: UKP Lab, Technische Universität Darmstadt (Germany)
 
−
* Title: PhD-position in NLP/Text Mining
 
−
* Natural Language Processing, Text Mining
 
−
* Location: Darmstadt (Germany)
 
−
* Deadline: open until the position is filled
 
−
* Date Posted: March 4, 2015
 
−
* Contact:  Richard Eckart de Castilho (eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de)
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The Ubiquitous Knowledge Processing Lab (UKP Lab) at the Department of Computer Science of the Technische Universität (TU) Darmstadt, Germany, has an opening for a PhD student (TV-TU E13 German payscale) in a research project in Natural Language Processing (NLP) for a computer scientist or computational linguist. The project focusses on building an open text-mining infrastructure at the European level (Principal Investigator: Prof. Dr. Iryna Gurevych).
 
−
 
 
−
Thereby, major NLP and Text Mining platforms, including UIMA and GATE, should be made interoperable and applied to knowledge discovery in scientific literature, e.g. entity disambiguation and linking to a background knowledge repository. In the past, the UKP Lab has developed several frameworks such as the Darmstadt Knowledge Processing Repository (DKPro) and UBY. They form the foundation for the research and implementation work to be done. The graduate program Knowledge Discovery in Scientific Literature provides further research environment for the work to be carried out.
 
−
 
 
−
'''Requirements'''
 
−
 
 
−
Applicants in Computer Science or Computational Linguistics must have demonstrable experience in designing and implementing complex natural language processing (NLP) systems or NLP-based applications and the programming language Java as well as strong research skills. Excellent communication skills in English and the ability to work in a team are required. Experience in open-source software development is a plus.
 
−
 
 
−
The following academic qualification is necessary: completion of an M.A./M.Sc. in Computer Science, Computational Linguistics, or a related field.
 
−
 
 
−
Pending the successful completion of the ongoing administrative steps for the project, funding of this position is available from June 1st, 2015 for the duration of three years.
 
−
 
 
−
Applications should include a CV, a motivation letter, an outline of research experience, as well as names and addresses of two referees.
 
−
 
 
−
Interviews may start at any time and will continue until the position has been filled. Email address for inquiries and applications: eckart (at) ukp (dot) informatik (dot) tu-darmstadt (dot) de
 
−
 
 
−
The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. The UKP Lab is also home to the unique research initiative "Knowledge Discovery in the Web” which emphasizes natural language processing, text mining, machine learning, as well as scalable infrastructures for assessment and aggregation of knowledge.
 
−
 
 
−
The Technische Universität Darmstadt promotes gender equality and in particular encourages women to apply. Preference will be given to physically handicapped persons if they are equally qualified.
 
−
 
 
−
 
 
−
==Internship position available in Natural Language Processing at Adobe Research==
 
−
* Employer: Adobe Systems Incorporated
 
−
* Title: NLP Scientist Intern
 
−
* Natural Language Processing, Machine Learning, Dialog Systems.
 
−
* Location: San Jose, CA
 
−
* Deadline: open until the position is filled
 
−
* Date Posted: February 24, 2015
 
−
* Trung Bui: bui@adobe.com
 
−
 
 
−
'''Description''':
 
−
We are looking for an NLP scientist intern who will work on exploring deep learning for mapping between natural language queries and logic form and/or SQL.
 
−
 
 
−
'''Key Qualifications'''
 
−
*Experience with semantic parsing, dialog systems.
 
−
*Experience with machine learning, deep learning.
 
−
*Good programming skills in Java and/or Python
 
−
 
 
−
'''Education'''
 
−
M.S. or PhD student in Computer Science or related field
 
−
 
 
−
'''Additional Requirements'''
 
−
No.
 
−
== Postdoc in Advanced Machine Learning (with an Emphasis on NLP) ==
 
−
 
 
−
*Employer:  University of Notre Dame
 
−
*Job Number:  4015639
 
−
*Date Posted:  02/17/2015
 
−
*Application Deadline: Open Until Filled
 
−
*Online application: http://www.postdocjobs.com/jobs/jobdetail.php?jobid=4015639
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The Computer Science Department at the University of Notre Dame in collaboration with the Institute for Intelligent Systems at the University of Memphis anticipates hiring a postdoctoral fellow starting as early as April 1st 2015 for one year and renewable for a second year. The position includes a full time salary and benefits and is jointly funded by sponsored research split between the University of Notre Dame and the University of Memphis. Review of applications will start immediately and continue until the position is filled.
 
−
 
 
−
The successful candidate will conduct research in machine learning applied to dialog-centered natural language understanding. He/she will participate in the development and application of machine learning techniques in the hierarchical and temporal domains to multi-party speech data collected in authentic educational contexts.
 
−
 
 
−
The candidate will work under the supervision of Dr. Sidney D’Mello, who has joint appointments in the Departments of Computer Science and Psychology at Notre Dame, and Dr. Andrew Olney in the Institute for Intelligent Systems at the University of Memphis.
 
−
 
 
−
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within a multi-department multi-institution grant-funded project. The postdoc will be encouraged to build advanced technical skills, strengthen their research portfolios via peer-reviewed publications, develop leadership skills by mentoring students, and gain expertise in authoring collaborative grant proposals.
 
−
 
 
−
'''Required'''
 
−
 
 
−
(1) Ph.D. in Computer Science, Artificial Intelligence, or a related field at the time of hire; (2) Research experience in advanced machine learning techniques for sequential and hierarchical domains (e.g., probabilistic graphical models, sequence tagging, deep learning) ; (3) Evidence of a strong publication record in the aforementioned areas
 
−
 
 
−
'''Desired'''
 
−
 
 
−
(1) Research experience in one or more of the following research areas (acoustic signal processing, automatic speech recognition, natural language understanding, discourse modeling) ; (2) Experience working on interdisciplinary projects and/or on educational research; (3) Experience mentoring graduate and undergraduate students
 
−
 
 
−
For more information see the application link above.
 
−
 
 
−
== Software Engineer/NLG Specialist in Sydney, Aus - Natural Lanaguage Generation==
 
−
*Employer: Macquarie Group
 
−
*Title: Software Engineer/NLG Specialist
 
−
*Specialties: Natural Language Generation, Application Development, Linguistics
 
−
*Location: Sydney, Australia
 
−
*Date posted: 29 January 2015
 
−
*Contact information: andy.logan@macquarie.com
 
−
*Online application: http://www.careers.macquarie.com/cw/en/job/923649/software-engineers-nlpnlg-programming-equities-research
 
−
 
 
−
'''Job Description'''
 
−
*Unique opportunity within the Equities Research space for a Engineer with strong NLG experience
 
−
*New Systems Implementation with Opportunity to push the envelope within Research
 
−
*Permanent Opportunity – Sydney CBD Location
 
−
 
 
−
'''About the role'''
 
−
 
 
−
We are seeking a Software Engineer to join our Equities Research business team. This is a truly unique opportunity for someone to join Macquarie working on a pioneering project within the business which could be a big game changer. The role will utilise your strong NLG/NLP experience and you will be responsible for building and developing the NLG functionality within the team. If you are interested in gaining commercial experience with NLG, have excellent written communications and have a flair for English grammar, have a passion for finance and in particular Equities Trading and want the opportunity to really pioneer something, then this could be the position for you.
 
−
 
 
−
'''Key Responsibilities'''
 
−
*Design and Develop our first NLG/NLP Application within Equities Research
 
−
*Work closely with the vendor to understand the application limitations and functionality
 
−
*Drive the development with the Head of Research as well as industry analysts
 
−
*Mature the offering and look for further areas of development within the business
 
−
 
 
−
'''About You'''
 
−
 
 
−
To be successful in this role as a Software Engineer you will possess a University Degree in Computer Science/Mathematics and would have probably undertaken further studies of some sort (Masters/PhD) and have previous Natural Language Generation/Processing experience in either a commercial or research environment. You will have a passion and flair for the English Language as well as having a interest in financial services and in particular traded products. Previous OO Development experience would be highly regarded. In addition you will possess the following:
 
−
 
 
−
*Tenacity to produce different If Statements and to develop the platform further
 
−
*Strong interest in Artificial Intelligence/Machine Based Learning.
 
−
*Keen interest in finance
 
−
*Self Starter and strong attention to detail to really drive uptake of the platform
 
−
 
 
−
This is a unique opportunity within Macquarie and quite possibly a pioneering project within the Investment Banking space. We are looking to hire two developers into the team and are flexible across career levels from recent Grads to Senior Engineers. Here at Macquarie we truly believe in you owning your future, at Macquarie you’ll own it. Find out more at the new Careers website: '''macquarie.com/career'''
 
−
 
 
−
If you meet the above requirements, please apply via the following link.  Alternatively to find out more about the position and a confidential discussion, please contact '''Andy Logan on 02 8237 8472 or andy.logan@macquarie.com'''
 
−
 
 
−
== PostDoc Position in Heidelberg (NLP, Networks, Databases, Machine Learning)==
 
−
*Employer: Heidelberg Institute for Theoretical Studies gGmbH (HITS)
 
−
*Title: PostDoc
 
−
*Specialties: Natural Language Processing, Networks, Databases, Machine Learning
 
−
*Location: Heidelberg, Germany
 
−
*Deadline: 20 February 2015
 
−
*Date posted: 29 January 2015
 
−
*Contact information: michael.strube (at) h-its.org
 
−
*Online application: https://application.h-its.org/intern/register.php?id=o51kdq1
 
−
 
 
−
'''Job Description'''
 
−
PostDoc position available in the NLP group at the Heidelberg Institute for Theoretical Studies (HITS) in Heidelberg, Germany
 
−
 
 
−
One position is available for a PostDoc working in Natural Language Processing, in particular in the areas of Entity Linking, Cross-document Coreference Resolution, Coreference Resolution, Word Sense Disambiguation. The position is within a newly funded project on "Scalable Author Name Disambiguation in Bibliographic Databases". Project partners are DBLP (http://dblp.org/db/) and zbMATH (https://zbmath.org/), the two leading bibliographic databases in computer science and mathematics which will also supply the data to be disambiguated and the gold standard. The project will be funded for three years starting June 1st, 2015.
 
−
 
 
−
The candidate should have a strong background in Natural Language Processing and possess a PhD in either Computational Linguistics or Computer Science. Experience with machine learning, databases, parallel programming, big data and networks as well as strong programming skills are required.
 
−
 
 
−
HITS gGmbH is a private non-profit research institute carrying out multidisciplinary research in the computational sciences. It receives its base funding from the HITS Stiftung.
 
−
 
 
−
The NLP group (http://www.h-its.org/en/research/nlp/) at HITS is an interdisciplinary research group that works on applications in the area of discourse and dialogue, in particular coreference resolution, entity linking, automatic summarization, and knowledge extraction from semistructured input. The NLP group at HITS works closely together with the Computational Linguistics Department at the University of Heidelberg.
 
−
 
 
−
To apply, please enter your application via the following link: https://application.h-its.org/intern/register.php?id=o51kdq1 (reference Postdoc NLP HITS-01-2015)
 
−
 
 
−
Applications must be submitted by February 20, 2015. Please note that applications not submitted via the online system will not be considered. Inquiries about the position can be directed at Michael Strube (michael.strube (at) h-its.org).
 
−
 
 
−
 
 
−
==Postdoc position in Cardiff (NLP, IR, machine learning)==
 
−
*Employer: Cardiff University
 
−
*Title: Postdoc
 
−
*Specialties: Natural language processing, information retrieval, machine learning, distributional models, relation extraction, commonsense resoning
 
 
*Location: Cardiff, UK
 
*Location: Cardiff, UK
−
*Deadline: 3 February 2015
+
*Deadline: March 2, 2017
−
*Date posted: 9 January 2015
+
*Date posted: February 13, 2017
−
*Contact information: SchockaertS1@cardiff.ac.uk
+
*Contact: schockaerts1@cardiff.ac.uk
−
 
 
−
'''Job Description'''
 
  
−
Applications are invited for a postdoctoral research associate post in the School of Computer Science & Informatics at Cardiff University. This is a full-time, fixed-term post for 30 months, starting on 1 May 2015 or as soon as possible thereafter.  
+
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.  
  
−
The main aim of this project is to learn fine-grained semantic relations from large text corpora. Initially such relations will be obtained in an unsupervised way, by identifying semantic relations with spatial relations between vector-space representations. Subsequently, open-domain, supervised relation extraction methods will be developed which use the output of the unsupervised methods as training data. This research will be part of an ERC funded project on the use of semantic relations between natural language terms in logics for commonsense reasoning. You will work closely with Dr Steven Schockaert. You will possess a PhD in Computer Science or a closely related area, or have equivalent experience.
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
  
 
'''Essential criteria'''
 
'''Essential criteria'''
  
−
*Proven ability to undertake research in a relevant research area (e.g. natural language processing, information retrieval, machine learning) at an international level, as evidenced by research output.  
+
* Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
−
*Excellent programming skills (java or C/C++).  
+
* 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 demonstrable history of contributing to excellent publications in relevant top-tier conferences (e.g. ACL, EMNLP, SIGIR, CIKM, IJCAI, AAAI, ICML) and journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, ACM Trans. Information Systems, IEEE Trans. Knowledge and Data  Engineering).  
+
* A strong background in statistics and linear algebra.
−
*Proven ability to communicate specialist ideas clearly in English using written media.  
+
* Excellent programming skills.
−
*Excellent organisational skills with a proven ability to work independently and be self-managing, to prioritise your work and meet deadlines within the framework of an agreed programme.  
+
* Knowledge of current status of research in specialist field.
−
*A PhD in Computer Science or closely related area, or equivalent experience.
+
* 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.
  
−
'''Desirable criteria'''
+
'''Background about the university'''
  
−
*Knowledge of statistical natural language processing.  
+
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.  
−
*Knowledge of unsupervised and semi-supervised learning.  
 
−
*Knowledge of relation extraction.  
 
−
*Experience with analysing large text corpora using a high-performance computing environment.
 
−
*Experience with dimensionality reduction methods such as multi-dimensional scaling, singular-value decomposition, and non-negative matrix factorisation.
 
  
−
'''More information'''
+
'''Background about the project'''
−
For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 2972BR.
 
  
−
==Post‐Doctoral and all levels of Research Scientist at the Allen Institute for Artificial Intelligence==
+
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.  
−
*Employer: Allen Institute for Artificial Intelligence (AI2)
 
−
*Title: Post-doc/Research Scientist
 
−
*Specialties (one or more): Natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, question answering and explanation
 
−
*Location: Seattle, WA
 
−
*Deadline: N/A, we are hiring throughout 2015
 
−
*Date posted: 12/9/2014
 
−
*Contact information: ai2-info@allenai.org, allenai.org
 
  
−
'''Job Description'''
+
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.
  
−
The Allen Institute for Artificial Intelligence (AI2) is a non-profit research institute in Seattle founded by Paul Allen and headed by Professor Oren Etzioni.  The core mission of (AI2) is to contribute to humanity through high-impact AI research and engineering. We are actively seeking Post Docs and Research Scientists at all levels who are passionate about AI and who can help us achieve this core mission by teaming to construct AI systems with reasoning, learning and reading capabilities.
+
'''More information'''
  
−
'''Position Summary'''
+
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.
  
−
AI2 currently has projects in the following areas:
+
==  Research Associates in Natural Language Processing / Text Mining,  University of Manchester, UK ==
−
*Language and Vision
+
*Employer: National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester, UK
−
*Information extraction and semantic parsing
+
*Title: Research Associates in Natural Language Processing / Text Mining
−
*Question answering
+
*Speciality: Natural Language Processing, Text Mining
−
*Language and reasoning
+
*Location: Manchester, UK
−
*Machine learning and theory formation
+
*Deadline: March 13, 2017
−
*Semantic search
+
*Date posted: February 10, 2017
−
*Diagram understanding
+
*Contact: sophia.ananiadou@manchester.ac.uk
−
 
 
−
AI2 Research Scientists will have a primary focus in one of these specific areas but will also have the opportunity to contribute and engage in a variety of other areas critical to our research and mission.  These include opportunities to participate in or lead select R&D projects, work with management to develop the long term vision for knowledge systems R&D, take a leading role in overseeing and implementing software systems supporting the research, author and present scientific papers and presentations for peer-reviewed journals and conferences, and help develop collaborative and strategic relationships with relevant academic, industrial, government, and standards organizations.
 
−
 
 
−
'''Applicant'''
 
−
 
 
−
Applicants for Research Scientist at AI2 should have a strong foundation (typically PhD level) in one or more of the following areas: natural language processing, machine reading, automatic knowledge base construction, large-scale textual inference and entailment, knowledge representation and reasoning, or question answering and explanation. We look favorably upon extensive work experience demonstrating application of your research.
 
−
 
 
−
'''Application Process'''
 
  
−
All candidates are required to submit a resume, an expression of interest, and the names and contact information of at least 2 references (including email addresses) through our website: http://allenai.github.io/ai2website/jobs.html. We particularly welcome applications from women, people of color, members of the LGBT communities, and people with disabilities. Visa sponsorship is available.
+
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. 
  
−
==Multiple Tenure-Track Positions (w/focus in Data Analytics) at The Ohio State University Department of Computer Science and Engineering==
+
'''Skills'''
−
* Employer: The Ohio State University
 
−
* Title: Assistant/Associate/Full Professor
 
−
* Specialty: open, two positions in Data Analytics
 
−
* Location: Columbus, OH, USA
 
−
* Deadline: January 31, 2015 (Consideration starts November 2014)
 
−
* Date Posted: November 17, 2014
 
−
* Website: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi
 
  
−
The Computer Science and Engineering Department at the Ohio State University expects to fill multiple tenure-track positions and seeks applicants in all areas of computer science.
+
You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus.  You should have excellent programming skills, preferably in Java.  
  
−
Particular emphasis will be placed on filling two open rank positions in conjunction with a broad university-wide research initiative on Data Analytics (https://discovery.osu.edu/focus-areas/data-analytics/collaborative.html), and a recently announced undergraduate program in Data Analytics (https://data-analytics.osu.edu). Areas of interest for these positions include (but are not limited to): data mining, big data management, cloud computing systems, data analytics; application of machine learning or data mining or data visualization to problems in network science (including social networks), health, and climate science.
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
−
The department is committed to enhancing faculty diversity; women, minorities, and individuals with disabilities are especially encouraged to apply.
+
'''Research Team'''
  
−
Applicants should hold or be completing a Ph.D. in CSE or a closely related field, have a commitment to and demonstrated record of excellence in research, and a commitment to excellence in teaching.
+
The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.
  
−
To apply, please submit your application via the online database. The link can be found at: https://web.cse.ohio-state.edu/cgi-bin/portal/fsearch/apply.cgi.
+
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).  
  
−
Review of applications will begin in November 2014 and will continue until the positions are filled.
+
Deadline of applications: 13/03/2017
  
−
The Ohio State University is an Equal Opportunity/Affirmative Action Employer.
+
Application forms and further particulars: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=12975

Revision as of 04:54, 10 June 2017

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

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


PhD position on data-driven methodologies for music knowledge extraction In the context of a collaborative project between the Music Technology and the Natural Language Processing groups of the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF) we offer a PhD position dedicated to developing data-driven methodologies for music knowledge extraction by combining Natural Language Processing and Music Information Retrieval approaches.

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

The work to be done in this PhD will aim at processing music related text from open web sources in order to generate musically relevant knowledge. For this, it will require combining methodologies coming from Music Information Retrieval (MIR), Natural Language Processing (NLP) and Computational Musicology.

The PhD position is part of the María de Maeztu Strategic Research Program on data-driven knowledge extraction (MDM-2015-0502) and linked to the program of the Spanish Ministry of Science and Competitiveness .


Scientific System Developer, UKP Lab, TU Darmstadt

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

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

to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners.

We ask for applications from candidates in Computer Science preferably with expertise in research and development projects, and strong communication skills in English and German. The successful applicant will work in projects including research activities in the area of Argument Mining (e.g. automatic evidence detection, decision support, large-scale web mining on heterogeneous source and data management), and development activities to create new products or industrial product prototypes. Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP) systems in Java and Python as well as experience in information retrieval, large-scale data processing and machine learning. Experience with continuous system integration and testing and distributed/cluster computing is a strong plus. Combining fundamental NLP research with industrial applications from different application domains will be highly encouraged.

UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.

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

Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: jobs@ukp.informatik.tu-darmstadt.de by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.

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


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

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

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

  • The focus of the first position will be on developing methods for exploiting entity embeddings in statistical relational learning, to enable robust plausible reasoning from sparse relational data. Entity embeddings can be used to identify plausible formulas that are missing from a given knowledge base, intuitively by applying a kind of similarity or analogy based reasoning. Statistical relational learning can also be used to infer plausible formulas, but instead relies on modelling statistical dependencies among relational facts at the symbolic level. Unifying both methodologies will allow us to develop powerful inference methods that combine their complementary strengths. The resulting method will be applied to zero and one shot learning tasks, with a focus on automated knowledge base completion.
  • The focus of the second position will be on learning vector space embeddings of events and the causal relations between them. In contrast to existing approaches, the learned embeddings will explicitly model which entities participate in the events, how they are related, and how their relationships are affected by different events. This will require combining ideas from neural network models for event embedding (e.g. based on LSTMs) with ideas from knowledge graph embedding models. Among others, the resulting model will allow us to uncover more intricate causal relationships, to generate supporting explanations for causal predictions, to incorporate prior knowledge, and to transfer learned knowledge between domains. Intended applications include recognising textual entailment, stock market prediction, and event-focused information retrieval.

Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)

Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available.


More information For more details about the positions, please contact Steven Schockaert (SchockaertS1@cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5878BR. Please note the requirement to evidence all essential criteria in the supporting statement.


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

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

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

The Institute of Cognitive Science (ICS) and Department of Computer Science at the University of Colorado Boulder anticipates hiring a full time postdoctoral fellow starting Summer/Fall 2017 for one year and renewable for a second year. The position includes a competitive salary commensurate with experience and full benefits. Review of applications will begin immediately and continue until the position is filled.

The postdoc will develop and apply machine learning techniques in the hierarchical and temporal domains to model behavioral and mental states (e.g., affect, attention, workload) from multimodal data (e.g., video, audio, physiology, eye gaze) across a range of interaction contexts (e.g., online learning, in-class learning, collaborative problem solving).

The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.

The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The postdoc will be encouraged to develop advanced technical skills, strengthen their research portfolios via peer-reviewed publications, gain interdisciplinary experience by working with a diverse team, develop leadership skills by mentoring students, and gain expertise in co-authoring grant proposals.

Required

  • Ph.D. in Computer Science, Artificial Intelligence, or a related field (at the time of hire)
  • Research experience in advanced machine learning for temporal and hierarchical domains (e.g., probabilistic graphical models, deep recurrent neural networks) applied to human behavior and mental state analysis (e.g., affective computing, dyadic/triadic interaction)
  • Self-motivated with a strong work ethic and writing proficiency as evidenced by a strong publication record

Desired

  • Research experience in one or more of the following areas (computer vision, eye tracking, computational psychophysiology, fMRI, multimodal fusion, collaborative problem solving, real-world sensing)
  • Experience mentoring graduate and undergraduate students

Job Details

  • 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.
  • Start date is negotiable, but anticipated for Summer/Fall 2017.
  • Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.

How to apply
Please complete Faculty/University Staff EEO Data (application) form (https://goo.gl/YC9g94) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.

Special Instructions to Applicants: The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.

The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at adacoordinator@colorado.edu.

Questions
Please email Dr. Sidney D’Mello


Researcher in Machine Learning and NLP, DFKI, Germany

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

The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.

Key research responsibilities include:

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

General responsibilities include:

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

Requirements:

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

The successful applicant will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University).

Working environment: DFKI is one of the largest AI research institutes worldwide, with several sites in Germany, covering basic research and applications. DFKI is a not-for-profit company with more than 500 researchers from 60+ countries across the globe. DFKI is based on a shareholder model including globally operating companies such as Intel, Google, Microsoft, Nuance, SAP, BMW, VW, Bosch, Deutsche Telekom, several SMEs, three German universities and three German Federal States.

The DFKI Multilingual Technologies lab partners in international, national and industry funded research projects in all areas of Language Technologies (including machine translation, question answering, information extraction, human-robot communication, speech and the multi-lingual web). The MLT lab currently leads the H2020 European Research project QT21 on MT, the EU CEF funded ELRC project and the EU funded TRADR project on human-robot collaboration in disaster response scenarios.

The MLT lab is part of the DFKI site at the Saarland University campus in Saarbrücken, Germany. Saarland University has exceptionally strong Computer Science and Computational Linguistics departments, two Max Plank Institutes in Computer Science, an Excellence Cluster in Multimodal Computing and Interaction and several International Doctoral and Master programmes in Computer Science and Computational Linguistics. DFKI staff regularly engage in teaching and supervision at Saarland University.

Geographical environment: Saarbrücken is the capital of Saarland with approximately 190,000 inhabitants. It is located right in the heart of Europe and is the cultural center of this border region of Germany, France and Luxembourg. Some of the closest larger cities are Trier, Nancy, Mannheim, Karlsruhe and Frankfurt. Paris can be reached by train in just under 2 hours. Living costs are modest in comparison with other large cities in Germany and elsewhere in Europe.

Starting date, duration, salary: Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.

Application: Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to Prof. Josef van Genabith referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact Prof. van Genabith for informal inquiries.


Associate Research Scientist, UKP Lab, TU Darmstadt

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

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

Associate Research Scientist
(PostDoc- or PhD-level; for an initial term of two years)

to strengthen the group’s profile in the areas of Interactive Machine Learning (IML) or Natural Language Processing for Language Learning. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Interactive Machine Learning and Natural Language Processing for Language Learning are the focus areas researched in collaboration with partners in research and industry.

We ask for applications from candidates in Computer Science with a specialization in Machine Learning or Natural Language Processing, preferably with expertise in research and development projects, and strong communication skills in English and German.

  • The successful applicant in the area of Interactive Machine Learning will work on research activities regarding its application to end-user content annotation, information structuring and recommendation, or semantic text analysis, and development activities to create functional and attractive user-oriented product prototypes.
  • The successful applicant in the area of Natural Language Processing for Language Learning will work on research activities in automatically assessing language competencies and readability as well as on generating exercise material for language learners in intelligent real-time learning systems.

Prior work in the above areas is a definite advantage. Ideally, the candidates should have demonstrable experience in designing and implementing complex (NLP and/or ML) systems, experience in large-scale data analysis, large-scale knowledge bases, and strong programming skills incl. Java. Experience with neural network architectures and a sense for user experience design are a strong plus. Combining fundamental NLP research on Interactive Machine Learning or Natural Language Processing with practical applications in different domains including education will be highly encouraged.

UKP’s wide cooperation network both within its own research community and with partners from research and industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique research initiative "Knowledge Discovery in the Web" and the Research Training Group "Adaptive Information Processing of Heterogeneous Content" (AIPHES) funded by the DFG emphasize NLP, machine learning, text mining, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.

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

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

Postdoctoral Fellowship in Linguistics and Cognitive Science at Northwestern University

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

The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).

The fellow will join a vibrant interdisciplinary community of researchers from across the cognitive sciences (including communication sciences, computer science, learning sciences, music cognition, neuroscience, philosophy, and psychology). The fellow’s research will be supported by the facilities of the Department of Linguistics.

To receive fullest consideration, applications should arrive by April 1, 2017. Candidates must hold a Ph.D. in Linguistics or a related field (e.g., Cognitive Neuroscience, Cognitive Science, Computer Science, Philosophy, Psychology, Speech and Hearing Sciences) by the start date. Please include a CV that includes contact information, brief statements of research and teaching interests (1-3 pages each), up to 3 reprints or other written work (including thesis chapters for ABD applicants), teaching evaluations (if available), and the names and contact information for three references. Please visit http://www.linguistics.northwestern.edu/ for online application instructions.

E-mail inquiries should be directed to Matt Goldrick, Chair of the Department of Linguistics (matt-goldrick@northwestern.edu). Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.

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

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

Applications are invited for a Postdoctoral Research Associate post in Cardiff University’s School of Computer Science & Informatics. This is a full-time, fixed-term post for 30 months, starting on 1 May 2017 or as soon as possible thereafter. The successful candidate will be dedicated to finding creative solutions and have a genuine curiosity and enthusiasm to undertake world-class research in the field of Machine Learning / Artificial Intelligence. Specifically, the aim of this post will be to develop novel methods for learning interpretable/symbolic models from diverse sources of information, including knowledge graphs, vector space models and natural language text. These models will then be used as background theories in applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning. You will work closely with Steven Schockaert. You will possess or be near the completion of a PhD in Computer Science or a related area, or have relevant industrial experience.

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

Essential criteria

  • Postgraduate degree at PhD level, or near to completion of a PhD in a related subject area or relevant industrial experience
  • An established expertise and proven portfolio of research and/or relevant industrial experience within at least two of the following research fields: Machine Learning, Knowledge Representation, Natural Language Processing.
  • A strong background in statistics and linear algebra.
  • Excellent programming skills.
  • Knowledge of current status of research in specialist field.
  • Proven ability to publish in relevant journals (e.g. Artificial Intelligence, Journal of Artificial Intelligence Research, Journal of Machine Learning Research, Machine Learning) or top-tier conferences (e.g. IJCAI, AAAI, ECAI, NIPS, ICML, KDD, ACL, EMNLP).
  • Ability to understand and apply for competitive research funding.
  • Proven ability in effective and persuasive communication.
  • Ability to supervise the work of others to focus team efforts and motivate individuals.
  • Proven ability to demonstrate creativity, innovation and team-working within work.

Background about the university

Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. Various surveys have ranked it as one of the most liveable cities in Europe. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. The school has a strong research track record recognised for its outstanding impact in terms of reach and significance, with 79% of its outputs deemed world-leading or internationally excellent in the 2014 Research Excellence Framework.

Background about the project

Vector space embeddings have become a popular representation framework in many areas of natural language processing and knowledge representation. In the context of knowledge base completion, for example, their ability to capture important statistical dependencies in relational data has proven remarkably powerful. These vector space models, however, are typically not interpretable, which can be problematic for at least two reasons. First, in applications it is often important that we can provide an intuitive justification to the end user as to why a given statement is believed, and such justifications are moreover invaluable for debugging or assessing the performance of a system. Second, the black box nature of these representations makes it difficult to integrate them with other sources of information, such as statements derived from natural language, or from structured domain theories. Symbolic representations, on the other hand, are easy to interpret, but classical inference is not sufficiently robust (e.g. in case of inconsistency) and too inflexible (e.g. in case of missing knowledge) for most applications.

The overall aim of the FLEXILOG project is to develop novel forms of reasoning that combine the transparency of logical methods with the flexibility and robustness of vector space representations. For example, symbolic inference can be augmented with inductive reasoning patterns (based on cognitive models of human commonsense reasoning), by relying on fine-grained semantic relationships that are derived from vector space representations. Conversely, logical formulas can be interpreted as spatial constraints on vector space representations. This duality between logical theories and vector space representations opens up various new possibilities for learning interpretable domain theories from data, which will enable new ways of tackling applications such as recognising textual entailment, automated knowledge base completion, or zero-shot learning.

More information

For more details about the project and instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 5545BR. Please note the requirement to evidence all essential criteria in the supporting statement.

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

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

The School of Computer Science, National Centre for Text Mining at the University of Manchester seeks to appoint two Research Associates in Natural Language Processing-based Text Mining to expand its text mining research portfolio.

They will join a strong team of 12+ staff who work on numerous national and international research projects, including industry, in areas of information extraction, disambiguation, topic analysis, natural language processing, biomedical text mining and machine learning.

Skills

You should have a PhD in Computer Science with an emphasis on Natural Language Processing and Text Mining. The focus of your research will be in developing (semi)-supervised methods for information extraction, in particular relation, event extraction and normalisation; a proven ability to develop algorithms for NLP/text mining problems using deep learning will be highly desirable; knowledge of developing text mining workflows using UIMA based environment will be a plus. You should have excellent programming skills, preferably in Java.

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

Research Team

The National Centre for Text Mining (http://www.nactem.ac.uk) has been a leading centre for text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems. NaCTeM is located in the Manchester Institute of Biotechnology (http://www.mib.ac.uk) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the "best environment in the UK for computer science and informatics research”.

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

Deadline of applications: 13/03/2017

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

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