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* See also the [http://linguistlist.org/jobs/index.html Linguist Job List].
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* See also the [http://linguistlist.org/jobs Linguist Job List].
 
* Archived postings:
 
* Archived postings:
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** [[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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== NLP-Speech Data Scientist / Civis Analytics / Chicago, IL, USA ==
+
* Employer: Universitat Pompeu Fabra [https://www.upf.edu/en/web/etic], Barcelona, Spain
 +
* Title: PhD Scholarship
 +
* Specialty: Text Mining, Information Extraction, Music Information Retrieval
 +
* Location: Barcelona, Spain
 +
* Deadline: Until candidate is found
 +
* Date posted: June 10, 2017
 +
* Contact: [mailto:horacio.saggion@upf.edu]
  
−
* Employer: Civis Analytics
 
−
* Title: Data Scientist
 
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* Specialty: Natural Language Processing / Speech Processing / Machine Learning
 
−
* Location: Chicago, Illinois, USA
 
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* Deadline: Rolling
 
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* Date Posted: July 7, 2014
 
  
−
'''Who We Are:'''
+
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 .
  
−
Our Company is a Chicago-based Big Data analytics firm born in a large windowless back room of President Obama’s 2012 re-election campaign. We called it “The Cave.”
 
  
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Beginning with the campaign, our mission as a team has been clear: help great organizations use their Big Data to solve their biggest problems.  We are now applying our analytical expertise, specialized software, and innovative technological approach to help companies, non-profits, and campaigns leverage their data to develop smarter strategies, make better decisions, and build stronger, data-driven organizations. In the year since our company’s founding, we have helped solve problems as diverse as enrolling individuals for health insurance, optimizing TV ad purchases to reach more targets, and pinpointing individuals who want to sign up for a clean energy utility company.
 
  
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We are not a group of spreadsheet management consultants; we are an inventive team of the best statisticians, scientists, engineers, and technologists in our fields building things that have never been built before. And we’re looking to add to our team.
+
== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
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We are already solving some of the world’s most demanding and complex problems with Big Data – working with organizations to analyze and understand their individual level intelligence to improve outcomes and implement organizational change. We work on teams with diverse skill sets to apply and invent new data science techniques, putting us at the forefront of innovation in our field as we solve problems that have never been solved before.
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
 +
* Title: Scientific System Developer
 +
* Specialty: Argument Mining, Machine Learning, Big Data Analysis
 +
* Location: Darmstadt
 +
* Deadline: May 31, 2017
 +
* Date posted: May 3, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
  
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We are smart, fun, and a little bit weird. Does this sound like you?
+
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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'''Job Description:'''
+
'''Scientific System Developer'''<br>
 +
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
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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.
+
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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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 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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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.
+
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.
  
−
'''Minimum Qualifications:'''
+
Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).
  
−
* Master’s degree in a quantitative field, such as computer science, statistics, machine learning, or electrical engineering, or a Bachelor’s degree and outstanding work experience
+
Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.
−
* 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)
 
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* Experience with common toolkits for unstructured data analysis, such as Theano, Torch, open-cv, the Stanford NLP tools, HTK, and Kaldi
 
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* Experience with SQL databases
 
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* Strong programming skills
 
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* Experience identifying and correcting for problems in imperfect data
 
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* An ability and eagerness to constantly learn and teach others
 
  
−
'''Preferred Qualifications:'''
+
Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297
−
* PhD in a quantitative field such as computer science, statistics, machine learning, or electrical engineering
+
We look forward to receiving your application!
−
* Ability to expand upon modern statistical learning methods
 
−
* 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
 
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* Familiarity with architectures for scaling statistical computing to big data applications, such as Hadoop and Spark
 
−
* Theoretical understanding sufficient to independently implement complex neural network architectures
 
  
−
'''Location:'''
 
  
−
This posting is for a position in Civis’ Chicago headquarters.
+
== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
  
−
'''Dates:'''
+
* 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]
  
−
We are hiring for multiple positions and will evaluate candidates as applications are received.
+
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.  
  
−
'''How to Apply:'''
+
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)
  
−
Applications may be submitted at http://www.civisanalytics.com/apply/entry/data-scientist-chicago-il.
+
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.  
−
Specific inquiries may be directed to Derrick Higgins: [mailto:dhiggins@civisanalytics.com dhiggins@civisanalytics.com].
 
  
  
−
== Postdoc in Natural Language Processing / Aix-Marseille University / Marseille, France ==
+
'''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.
  
−
* Employer: Aix-Marseille University
 
−
* Title: Postdoc
 
−
* Specialty: Natural Language Processing
 
−
* Location: Luminy, Marseille, France
 
−
* Deadline: July 1st, 2014
 
−
* Date Posted: June 12, 2014
 
  
−
'''Job Description:'''
+
== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
  
−
We are looking for an outstanding research scientist to join the "SENSEI" european project (http://www.sensei-conversation.eu/). You
+
* Employer: University of Colorado Boulder
−
will contribute to conversation analysis summarization research to
+
* Title: Postdoctoral Research Associate
−
allow the exploitation of large quantity of comments in social
+
* Specialty: Advanced Machine Learning
−
media and spoken conversations.
+
* Location: Boulder, Colorado, United States
 +
* Deadline: Ongoing, desired start Summer/Fall 2017
 +
* Date posted: March 31, 2017
 +
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
−
You will contribute to the design and development of speech and text
+
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
−
summarization technologies for conversational data such as social
+
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
−
media comments and tweets. There will be three components to the
 
−
system: linguistic analysis of the conversations, content selection
 
−
and aggregation, and generation of the summaries (text or other
 
−
media). The approach is expected to make use of recent machine
 
−
learning advances such as deep learning, and focus on limiting the
 
−
quantity of supervision needed. The prototype will be evaluated by
 
−
end-user professionals in ecological conditions.
 
  
−
'''Qualifications:'''
+
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 applicant must hold a PhD degree, preferably in the field of
+
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).
−
natural language processing or machine learning. He/she should:
 
−
* Be proficient in one of Java / C++ programming and python or php scripting
 
−
* Have experience with developing efficient NLP / machine learning systems.
 
−
* Be keen on researching the literature and writing papers
 
−
* Enjoy team work and be autonomous
 
  
−
'''Location:'''
+
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.
  
−
You will work at the LIF computer science lab at Aix-Marseille
+
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.
−
University in France, at the Luminy campus next to the
 
−
calanques.
 
  
−
'''Dates:'''
+
'''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
  
−
Interviews will be held in July 2014, the Postdoc will start in
+
'''Desired'''
−
september / october 2014 and last one year.
+
* 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
  
−
'''How to Apply:'''
+
'''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.
  
−
Enquiries and applications should be sent to Benoit Favre: benoit.favre@lif.univ-mrs.fr
+
'''How to apply''' <br/>
 +
Please complete Faculty/University Staff EEO Data (application) form ([https://goo.gl/YC9g94 https://goo.gl/YC9g94]) and upload the following required documents: 1—Cover letter; 2—Curriculum Vitae 3—List of Three References 4-One or two representative publications.
  
−
== Executive Director / CLARIN ERIC / Utrecht University, the Netherlands ==
+
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.
  
−
* Employer: CLARIN ERIC through Utrecht University
+
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].
−
* Title: Executive Director
 
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* Specialty: Research Infrastructures
 
−
* Location: Utrecht University, the Netherlands
 
−
* Deadline: August 15, 2014
 
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* Date Posted: June 10, 2014
 
  
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'''Job Description:'''
+
'''Questions''' <br/>
 +
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
−
CLARIN is one of the two big humanities pan-European research infrastructures on the ESFRI roadmap with global ambitions, expected to expand rapidly in the near future. It currently has about 25 centres in 10 countries and the number is growing. At the same time CLARIN is participating actively in several emerging global data infrastructure initiatives (e.g. RDA, EUDAT). In addition it is actively pursuing its collaboration with other international humanities research infrastructures such as DARIAH.
 
  
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As our current Executive Director is retiring, CLARIN is looking for an inspiring person to continue this successful enterprise and lead it to the next level.
+
== Researcher in Machine Learning and NLP, DFKI, Germany ==
  
−
The main challenges the new executive director needs to lead on in the next years are: the expansion and the sustainability of CLARIN, to balance the central and distributed activities, increase outreach to new user communities, new collaboration partners and new continents, and to promote collaboration with commercial partners.  
+
* Employer: [http://www.dfki.de/ DFKI GmbH], Germany
 +
* Title: Researcher
 +
* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
 +
* Location: Saarbruecken
 +
* Deadline: March 31, 2017
 +
* Date posted: March 13, 2017
 +
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]
  
−
'''Responsibilities:'''
+
The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.
  
−
* Leading the Board of Directors of the CLARIN ERIC
+
'''Key research responsibilities''' include:
−
* Building on prior work, drafting strategy, work programme, budget and staff plan for CLARIN
+
* machine and deep learning for natural language processing/machine translation
−
* Planning the technical development together with the Technical Director, overseeing the implementation and operation of the distributed infrastructure and coordinating centre cooperation
+
* software development and integration
−
* Ensuring the long-term sustainability of CLARIN and guiding its European and global expansion
+
* publication in top-tier conferences and journals
−
* Building strong pan-European and international relationships with a broad range of stakeholders within and outside the consortium. This includes CLARIN members, the relevant ministries and funding bodies, external language resource providers, the EU, and international bodies, including research infrastructures on the European Strategy Forum on Research Infrastructures (ESFRI) Roadmaps as well as other research infrastructures
 
−
* Leading the international fundraising efforts for CLARIN
 
−
* Monitoring and measuring CLARIN’s activities and reporting to General Assembly
 
−
* Specifically, monitoring the adherence of the national consortia to the operational rules and standards for CLARIN-related operations, and developing recommendations for counter-measures for any irregularities
 
−
* Ensuring that CLARIN’s services comply with appropriate ethical, legal and societal norms and principles
 
−
* Planning, organizing, and managing the main office in Utrecht, which includes recruitment
 
−
* Facilitating and supporting the operation of CLARIN’s governance bodies
 
  
−
'''Qualifications:'''
+
'''General responsibilities''' include:
−
 
+
* engagement with industry partners and contract research  
−
* A higher university degree or equivalent qualifications and an international interdisciplinary network
+
* identification of funding opportunities and engagement in proposal writing
−
* Relevant experience in the European Research Area, international arena, as well as in European level funding mechanisms and understanding of the ESFRI process
+
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations
−
* An understanding of current and emerging agendas and challenges in data management and curation in the humanities domain
+
* administrative work associated with programmes of research
−
* Excellent communicative skills
 
−
* A proven fundraising record
 
−
* A record of relevant academic excellence
 
−
* The ability to understand organisational and technical issues involved in building, maintaining, and federating digital repositories, catalogues, authentication services, and similar infrastructure components based on modern information technologies
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
For more information, please visit http://www.clarin.eu/news/vacancy-advertisement-executive-director
 
−
 
 
−
 
 
−
== Research Scientist in Natural Language Technologies / Bosch Research & Technology Center / Palo Alto, California ==
 
−
 
 
−
* Employer: Bosch Research & Technology Center
 
−
* Title: Research Scientist in Natural Language Technologies (PhD)
 
−
* Specialty: Natural Language Processing
 
−
* Location: Palo Alto, California, United States, 94304
 
−
* Deadline: Until filled
 
−
* Date Posted: May 19, 2014
 
−
 
 
−
'''Job Description:'''
 
−
 
 
−
The Language Interaction and Knowledge Engineering group of Bosch Research in Palo Alto, CA is responsible for shaping the future user experience of Bosch products by creating cutting-edge technologies. We collaborate closely with leading universities on solutions to hard challenges in speech, language, knowledge topics to enable natural, intuitive and intelligent communication between humans and computers.  We work with internal partners to transfer our ideas and solutions into future products. Over the years, we have already developed innovative world-leading technologies in the areas of human machine interaction (HMI) systems.
 
−
 
 
−
To strengthen the Language Interaction and Knowledge Engineering team in our Palo Alto office we are seeking enthusiastic and creative researcher with a strong desire to drive technology development in this area.
 
−
 
 
−
'''Responsibilities:'''
 
−
 
 
−
* Develop large-scale natural language technologies and components, and improve the state-of-the-art HMI system performance with various methods
 
−
* Together with a team of experts, adapt and integrate language processing components into Bosch HMI system for different business areas
 
−
* Communicate with business departments about the technology potentials as well as identify potential areas of business values.
 
−
 
 
−
 
 
−
'''Qualifications:'''
 
−
 
 
−
* Ph.D. in Computer Science or related fields
 
−
* Strong research background in natural language technology development and applications, text mining, machine learning, and statistics
 
−
* Hands-on experience with natural language processing, text mining and machine learning algorithm implementation
 
−
* Strong skills in coding (C/C++ or Java), algorithms and system design
 
−
* Very good communication skill together with good quality publication
 
−
* Experience in text summarization research and development is a plus
 
−
* Experience in large system development and speech technology is a plus
 
−
 
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
For more information, and to apply online, please visit http://bit.ly/1k8UZ57
 
−
 
 
−
 
 
−
 
 
−
== Post-doc in Machine Learning, Computer Vision, Language Processing applied to Sign Language Analysis / TTI-Chicago / Chicago, IL ==
 
−
 
 
−
* Employer: Toyota Technological Institute at Chicago
 
−
* Title: Post-doctoral scholar
 
−
* Specialty: Machine learning, NLP, computer vision, speech
 
−
* Location: Chicago, IL, United States, 60637
 
−
* Deadline: Until filled
 
−
* Date Posted: May 12, 2014
 
−
 
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
Applications are sought for a post-doctoral position as part of a project on automatic sign language analysis and recognition. The post-doc will work primarily with TTI-Chicago (TTIC) faculty Greg Shakhnarovich and Karen Livescu. The work is part of a broad interdisciplinary project including both recognition and linguistics of American Sign Language (ASL), in collaboration with U. Chicago linguistics faculty Diane Brentari and Jason Riggle. The post-doc will also have opportunities to collaborate with other TTIC and the University of Chicago researchers as relevant, and should be able to interact with colleagues in a broad range of disciplines.
 
−
 
 
−
 
 
−
The post-doc will be based at TTI-Chicago, a computer science graduate institute located on the University of Chicago campus, with vibrant research groups in machine learning, computer vision, and speech and language processing. The position is for 2 years, contingent on annual reappointment.
 
−
 
 
−
 
 
−
The target start date is Fall 2014, with some flexibility. Compensation includes a competitive salary and benefits plan.  The position will remain open until filled.
 
−
 
 
−
 
 
−
'''Responsibilities'''
 
−
 
 
−
The goal of the work is to advance automatic recognition and analysis of American Sign Language (ASL), in part through development of core methods for learning and vision. The specific focus of the post-doc's research will be determined by mutual agreement based on the post-doc's background and interests, and may include any of: new graphical models and learning techniques; articulated hand pose tracking and estimation constrained by the grammar of sign; domain adaptation/normalization for different subjects and signing styles; techniques inspired by speech recognition and NLP; and work with new data sources beyond video, including depth sensors (e.g. Kinect) and motion capture. Prior knowledge of and interest in ASL is preferred.
 
−
 
 
−
 
 
−
Advising and teaching opportunities are likely to be available if desired, but this is not a requirement of the position.
 
−
 
 
−
 
 
−
'''Qualifications'''
 
−
 
 
−
Applicants are expected to have strong qualifications in machine learning or related fields, and ideally also computer vision and/or speech and language processing. Applicants should have a PhD or expected PhD (by the end of 2014) in computer science, electrical engineering, statistics, or a related field.  There are no citizenship requirements.
 
−
 
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Please direct questions and interest in the position to ASL-postdoc@ttic.edu. Complete applications should be sent to the same address and consist of:
 
−
 
 
−
* brief cover letter, describing your interest in and qualifications for the position
 
−
* curriculum vitae including publication list
 
−
* contact information for two or more researchers who can provide letters of reference
 
−
 
 
−
Please see http://ttic.edu/livescu/ASL-postdoc.html for more information.
 
−
 
 
−
== Postdoctoral Fellow / INRIA / Saclay ==
 
−
* Employer: Institut National de Recherche dans l'informatique et l'Automatisme (INRIA)
 
−
* Title: PostDoc (12 months)
 
−
* Specialty: Natural Language Processing
 
−
* Location: Palaiseau, Ile-de-France, France
 
−
* Deadline: June 30, 2014
 
−
* Date Posted: May 6, 2014
 
−
 
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The principal mission of the postdoctoral candidate is to find new ways of inducing taxonomies and semantic dimensions from user generated and user captured personal data, integrating textual, quantified, geolocalized, image, sound and video data. The postdoc will also assist the TRACES team in developing algorithms and technology for creating a platform for private, personal information management.
 
−
 
 
−
'''Duties'''
 
−
 
 
−
Reporting to the Dr. Gregory Grefenstette, your
 
−
typical duties will include the following:
 
−
 
 
−
* Implement recent taxonomy/ontology induction algorithms, adapting them to the problem of personal information, applying them to personal data contributed by TRACES team members, evaluating results, and present their results in an international conference or workshop;
 
−
* Aid TRACES members in the construction of a private personal information platform based on open source information retrieval systems (Lucene/SolR);
 
−
* Discover and adapt existing open data taxonomies to the platform;
 
−
* Study how GPS information and other quantified personal data can be integrated into and augment the personal semantic structures induced from textual sources
 
−
 
 
−
 
 
−
'''Required Qualifications'''
 
−
 
 
−
The candidate must possess a recent PhD degree (granted 2013 or 2014) in computer
 
−
science, computational linguistics or a related discipline.
 
−
* Experience with natural language processing (e.g., Stanford Parser)
 
−
* Experience with ontologies/taxonomies (e.g., MeSH, FreeBase)
 
−
* Experience with classification algorithms
 
−
* Familiarity with dealing with large, noisy data sets
 
−
* Experience with web crawler, information retrieval systems (e.g., Lucene/Solr/ElasticSearch)
 
−
* Desire to produce functioning end-to-end systems, life-scale live demos
 
−
* Scientific rigour
 
−
* Imagination
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Follow the instructions on the page: http://www.inria.fr/en/institute/recruitment/offers/post-doctoral-research-fellowships/post-doctoral-research-fellowships/campaign-2014/(view)/details.html?ContractType=4546&LG=EN&nPostingID=8473&nPostingTargetID=14242
 
−
 
 
−
Security and Defense procedure: In the interests of protecting its scientific and technological assets, Inria is a restricted-access establishment. Consequently, it observes special regulations for welcoming foreign visitors from outside of the Schengen area. The final acceptance of each candidate thus depends on applying this security and defense procedure.
 
−
 
 
−
'''About Us'''
 
−
 
 
−
Public science and technology institution established in 1967, Inria is is the only public research body fully dedicated to computational sciences. Combining computer sciences with mathematics, Inria's 3,400 researchers strive to invent the digital technologies of the future. Educated at leading international universities, they creatively integrate basic research with applied research and dedicate themselves to solving real problems, collaborating with the main players in public and private research in France and abroad and transferring the fruits of their work to innovative companies. The researchers at Inria published over 4,800 articles in 2010. They are behind over 270 active patents and 105 start-ups. In 2010, Inria's budget came to 252.5 million euros, 26% of which represented its own resources..
 
−
 
 
−
For more information, please visit http://www.inria.fr/en/institute/recruitment/offers/post-doctoral-research-fellowships/post-doctoral-research-fellowships/campaign-2014
 
−
 
 
−
== Postdoctoral Fellow / Bioinformatics Technology Lab / Genome Sciences Centre ==
 
−
* Employer: University of British Columbia and BC Cancer Agency
 
−
* Title: PostDoc
 
−
* Specialty: Natural Language Processing, Machine Learning
 
−
* Location: Vancouver, British Columbia, Canada
 
−
* Deadline: Until filled
 
−
* Date Posted: March 26, 2014
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
The Genome Sciences Centre is seeking a Postdoctoral Fellow for the Bioinformatics
 
−
Technology Lab to conduct scientific research in the areas of bioinformatics and
 
−
genomics, specifically related to automated analysis and annotation of cancer
 
−
research literature.
 
−
 
 
−
The successful applicant will work with trainees and research scientists in a team
 
−
that develops tools for a clinical genomics pipeline based on primary sequence
 
−
analysis, to build natural language processing and machine learning tools that
 
−
interpret identified mutations for their biological significance as they relate
 
−
to reports in the relevant literature.
 
−
 
 
−
'''Duties'''
 
−
 
 
−
Reporting to the Head of Bioinformatics Technology Lab, Dr. Inanc Birol, your
 
−
typical duties will include the following:
 
−
 
 
−
* Building natural language processing and machine learning tools for automated literature survey
 
−
* Analysis and annotation of data from genomics studies as they relate to the literature
 
−
* Collaborating with biologists and clinical researchers on the accuracy of the results
 
−
* Reporting research methods and results in meetings, seminars and conferences
 
−
* Contribution to and leading scientific publications and research proposals
 
−
 
 
−
'''Required Qualifications'''
 
−
 
 
−
The ideal candidate should possess a PhD degree and recent proven experience in computer
 
−
science, electrical engineering or a related discipline. A strong publication record in
 
−
the field, and demonstrated technical writing skills are highly desirable. Prior research
 
−
experience in bioinformatics is also desirable, but not required.
 
−
 
 
−
More experienced candidates will be considered for a Staff Scientist position, pending
 
−
successful funding.
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Please send your resume with cover letter to bcgscjobs@bcgsc.ca
 
−
We request that you specify the position you are applying for by identifying the Job Code
 
−
only ("PDFBTL 14-03-27") in the subject line of your emailed application.
 
−
 
 
−
All qualified candidates are encouraged to apply; however, Canadian citizens and permanent
 
−
residents will be given priority.
 
−
 
 
−
'''About Us'''
 
−
 
 
−
Genome Sciences Centre is a leading international institution for genomics and bioinformatics
 
−
research. Our mandate is to advance knowledge about cancer and other diseases, to improve human
 
−
health through disease prevention, diagnosis and therapeutic approaches, and to realize the
 
−
social and economic benefits of genomics research.
 
−
 
 
−
For more information, please visit www.bcgsc.ca
 
−
 
 
−
== PostDoc / NLP, Machine Learning, Medical Informatics / Worcester MA ==
 
−
* Employer: University of Massachusetts Medical School
 
−
* Title: PostDoc
 
−
* Specialty: Natural Language Processing, Machine Learning
 
−
* Location: Worcester, Massachusetts, United States, 01605
 
−
* Deadline: Until filled
 
−
* Date Posted: March 26, 2014
 
−
 
 
−
 
 
−
'''Job Description'''
 
−
 
 
−
We are seeking 1~2 highly motivated postdoctoral research associate to
 
−
join the Biomedical Natural Language Processing (BioNLP) group at
 
−
UMass Medical School and UMass Amherst. This position will primarily
 
−
be located at the UMass Medical School in Worcester, MA. The BioNLP
 
−
group is actively pursuing many exciting projects including:
 
−
information retrieval, information extraction, summarization, question
 
−
answering, data mining, and patient-centered research. A highly
 
−
productive candidate may transition to a faculty position.
 
−
 
 
−
 
 
−
'''Responsibilities'''
 
−
 
 
−
The successful candidates will help investigate new algorithms to
 
−
support our current research thrusts. This will require extensive
 
−
experience with data mining (DM) and natural language processing (NLP).
 
−
 
 
−
 
 
−
'''Qualifications'''
 
−
 
 
−
Candidates for this position should have a PhD in Computer Science or
 
−
related field and a significant research record including
 
−
publications in top conferences and journals in:
 
−
 
 
−
* Natural Language Processing
 
−
* Machine Learning
 
−
* Data Mining or Data Analysis
 
−
 
 
−
Proficiency in quantitative analytical methods and strong programming
 
−
skills (e.g., python, matlab, java, C/C++, weka, etc.), along with
 
−
extensive research experience in hands-on machine learning (ML) and
 
−
data mining (DM), is essential. Additional experience in
 
−
bioinformatics or figure search and analysis is desirable.
 
−
 
 
−
Successful applicants will join a vibrant collaborative research
 
−
environment, will work closely with clinical investigators and senior
 
−
personnel in the lab, and should have the ability to work effectively
 
−
both independently and as part of a multidisciplinary team. The
 
−
position will be for one year, renewable annually, starting Summer or Fall 2014.
 
−
 
 
−
 
 
−
'''How to Apply'''
 
−
 
 
−
Please apply by email to Prof. Hong Yu <hong.yu@umassmed.edu> and
 
−
include a brief letter of introduction, a CV including list of
 
−
publications in PDF format, and names and email addresses of 2-3 referees.
 
−
 
 
−
 
 
−
'''Background'''
 
−
 
 
−
Please see http://www.bio-nlp.org/postdoc-ad-2014.txt for more information.
 
−
 
 
−
Competitive Salary based on experience.
 
−
 
 
−
== Research Director NLP and Speech Processing / Educational Testing Service / Princeton, New Jersey ==
 
−
 
 
−
* Employer: Educational Testing Service
 
−
* Title: Research Director NLP and Speech Processing
 
−
* Specialty: Natural Language Processing / Speech Processing
 
−
* Location: Princeton, New Jersey, United States, 08541
 
−
* Deadline: Until filled
 
−
* Date Posted: March 12, 2014
 
−
 
 
−
'''Job Description:'''
 
−
 
 
−
ETS (Educational Testing Service), is headquartered in Princeton, NJ. Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development.
 
−
 
 
−
Currently we are seeking a Research Director of the Natural Language Processing (NLP) and Speech Group to lead a team of 26 scientists and engineers in the research and development of innovative technologies to improve assessment. The Director also leads research that encourages the appropriate use of these technologies in operational settings and advances the state of the art in NLP and speech processing research in the education domain.
 
−
 
 
−
Specifically, you will be responsible for conceptualizing and pursuing a research agenda of fundamental and applied research in NLP and speech processing that will address current needs and anticipate future needs of education and assessment. This includes the development of technologies to automate or facilitate scoring of open-ended responses, support practices for developing tests and learning materials, safeguard the security and validity of assessments, enable technology-rich environments for assessment and learning, and provide automated performance feedback.
 
−
 
 
−
In addition, you will assume responsibility for the enhancement of a variety of existing ETS technologies that include e-rater (for automated scoring of essays), c-rater (for scoring content-based short answers), and SpeechRater (for scoring the spontaneous speech of English Language Learners), as well as the development of fundamentally new systems and methods.
 
−
 
 
−
Also, you be responsible for leading efforts to expand the use of ETS NLP and speech technologies. The Director will actively seek out opportunities for operational use of these technologies for both internal and external clients. This includes coordinating with ETS business units to understand market and client needs/trends, identify appropriate use contexts, develop the necessary research evidence to support operational use, and establish procedures for the transition of research technologies to production environments.
 
  
 
'''Requirements:'''
 
'''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
  
−
To qualify, you must possess:
+
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).
−
* A Doctoral degree in computer science, computational linguistics, linguistics, electrical engineering, or a related field
 
−
* Eight years of progressively more independent research experience providing evidence of continuing and substantial contributions to a field of study are necessary, with experience managing research staff and transitioning the outcomes of research into operational practice desirable.
 
−
* Excellent verbal and written communications skills, including public speaking, interpersonal and public relations skills, and writing and editing skills.
 
−
 
 
−
'''How to Apply:'''
 
−
 
 
−
Please apply online at: http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=160741&BUID=2538
 
−
 
 
−
'''Information about the institute:'''
 
−
 
 
−
We offer a competitive salary and excellent compensation package including medical, dental, vision, 403(b) retirement plan, life and disability insurance, paid time off and an employee assistance program.
 
−
 
 
−
With more than 3,400 global employees worldwide, ETS develops, administers and scores more than 50 million tests annually in more than 180 countries, at 9,000+ locations worldwide. In addition to assessments, we conduct educational research, analysis and policy studies and develop a variety of customized services and products for teacher certification, English language learning and elementary, secondary and postsecondary education. Equal Opportunity Employer
 
−
 
 
−
== Research Intern in Natural Language Processing (NLP) / Text Mining / Digital Humanities ==
 
−
 
 
−
* Employer: The Ubiquitous Knowledge Processing Lab (UKP Lab) in Darmstadt/Frankfurt
 
−
* Title: Research Intern
 
−
* Specialty: Natural Language Processing / Text Mining / Digital Humanities
 
−
* Location: Darmstadt/Frankfurt am Main, Germany
 
−
* Deadline: Until filled
 
−
* Date Posted: January 20, 2014
 
−
* Contact email: gurevych (at) cs (dot) tu-darmstadt (dot) de
 
−
 
 
−
'''Job Description:'''
 
−
 
 
−
The Ubiquitous Knowledge Processing Lab (UKP Lab) offers several exciting internship opportunities in cutting-edge research projects as
 
−
 
 
−
* Research Intern in Natural Language Processing (NLP) / Text Mining / Digital Humanities
 
−
 
 
−
located either at the Computer Science Department of the Technische Universität Darmstadt or at the Information Center for Education at DIPF in Frankfurt (Germany)
 
−
 
 
−
The positions are situated within one of the Lab’s projects dealing with automatic text processing, linguistic and machine learning based methods of language analysis, corpus development for novel tasks, or tool support for users in NLP research and humanities. The Lab’s approach to NLP features the hybrid methods in large-scale language processing, real-world text mining, and hands-on skills in the rapid development of scalable systems with practical relevance.
 
−
 
 
−
The position is a fixed-term internship contract (6 months) with an option to extend it up to 1 year, provided certain conditions are met. A part-time working arrangement is possible. The internships are funded according to the level of qualification, previous experience, and formal criteria.
 
−
 
 
−
'''Requirements:'''
 
−
 
 
−
We are looking for internship students to work on one of the following areas: computational linguistics, text mining, or machine learning, with substantial theoretical knowledge, excellent problem-solving and programming (Java) skills for language processing, eagerness to apply the knowledge and skills in new contexts, and interest to participate in the Lab’s internationally competitive research. The ability to work independently, personal commitment, teamwork and communication skills, and a readiness to cooperate are required. The ability to speak German as well as previous experience in NLP, text-mining, or digital humanities are beneficial, but is not a job requirement.
 
−
 
 
−
We welcome applications of students at all levels of study (bachelor, master) as well as graduate-level applications. The position is ideally suited to acquire research experience abroad (also as required by the ongoing study program of an applicant), or qualify as a Master-, PhD-student, or a research associate at one of the leading universities, and for a competitive industry position.
 
−
 
 
−
 
 
−
'''How to Apply:'''
 
−
 
 
−
Applications (including CV, details of previous academic work, at least two educational and professional references, and final thesis in electronic form) should be submitted to gurevych (at) cs (dot) tu-darmstadt (dot) de.
 
−
 
 
−
 
 
−
'''Information about the institute:'''
 
−
 
 
−
The Computer Science Department of the Technische Universität Darmstadt is regularly ranked among the best in Germany. The Ubiquitous Knowledge Processing Lab (UKP Lab) in Darmstadt/Frankfurt (http://www.ukp.tu-darmstadt.de/) led by Professor Iryna Gurevych offers an excellent research environment. The distinguishing features of its research are novel linked lexical semantic resources, algorithms for semantic language analysis (for example, word sense disambiguation, or semantic role labeling), and text-mining (for example, topic recognition, or opinion analysis). The ongoing research projects closely cooperate with users of the developed technologies in humanities, e.g. in educational research, text interpretation in philosophy, corpus linguistics, or history sciences. Within the graduate program “Knowledge Discovery in Scientific Literature” (http://www.kdsl.tu-darmstadt.de/), the UKP Lab is networked with multiple groups in machine learning, statistical NLP and information management.
 
−
 
 
−
 
 
−
== Research Scientist for Automated Language Processing / Text Mining / Digital Humanities, German Institute for International Educational Research (DIPF), Frankfurt am Main ==
 
−
 
 
−
* Employer: The German Institute for International Educational Research (DIPF)
 
−
* Title: Research Scientist
 
−
* Specialty: Automated Language Processing / Text Mining / Digital Humanities
 
−
* Location: Frankfurt am Main, Germany
 
−
* Deadline: February 14, 2014
 
−
* Date Posted: January 13, 2014
 
−
* Contact email: gurevych (at) dipf (dot) de
 
−
 
 
−
'''Information about the institute:'''
 
−
 
 
−
The German Institute for International Educational Research (DIPF) (http://www.dipf.de/) n Frankfurt am Main, Germany, is a member of the Gottfried Wilhelm Leibniz Association of Sciences. As a national centre for educational research and educational information, it is jointly funded by the federal government (Bund) and the states (Länder).
 
−
 
 
−
As a scientific institution and member of the Leibniz Association, DIPF targets high-quality fundamental research as well as a research-based development of innovative scientific services. It addresses education as a public domain with high visibility and high importance. By bringing together competencies, DIPF and Computer Science at TU Darmstadt are setting up a priority domain of knowledge processing and computer science in education. In relevant national rankings, the Computer Science department at TU Darmstadt regularly holds top positions. In 2012, the UKP-DIPF group was established: its unique features include semantic language processing, text mining and information retrieval as well as powerful infrastructures for evaluating and aggregating knowledge.
 
−
 
 
−
 
 
−
'''Job Description:'''
 
−
 
 
−
At DIPF, the research unit “Ubiquitous Knowledge Processing Lab“ at the Information Center for Education (located in Frankfurt am Main, Germany) is looking for an
 
−
 
 
−
* Research Scientist for Automated Language Processing / Text Mining / Digital Humanities (three-year contract, full time, EG13 TV-H*)
 
−
 
 
−
The position is situated in the context of the project “Die Welt der Kinder: Weltwissen und Weltdeutung in Schul- und Kinderbüchern zwischen 1850 und 1918“ [children’s worlds: knowledge and interpretation of the world in  textbooks and children’s books from 1850 to 1918], subject to the Leibniz competition for excellence. Here, DIPF collaborates with the Georg-Eckert Institute for International Textbook Research (Brunswick) and the Institute for Language Technology and Information Science (University of Hildesheim).
 
−
 
 
−
The project targets research into historical textbooks and children’s books - and the analysis of world views children grew up with. In the project, classical qualitative methods used in historical sciences to analyse texts that are charged with interpretation will be interlinked with automatic indexing and semantic annotation of historical sources by means of semantic language processing methods. First and foremost, Topic Detection and Opinion Mining methods will be explored and further developed. So far, no training data exist for the analysis of historical texts in German. Thus, the appointment addresses a genuine task in the context of innovative digital humanities, targeting the implementation of unsupervised and adaptive language processing methods. Another innovative aspect concerns the close collaboration with users and the linkage of intellectual with automated methods of analysis.
 
−
 
 
−
The position is integrated into a highly dynamic environment at DIPF and TU Darmstadt. At DIPF, the successful candidate will co-operate with researchers in the growing domain of “Ubiquitous Knowledge Processing”, with computer science and educational research groups and information services, e.g. the Research Library for  the History of Education (BBF) at DIPF. At TU Darmstadt, a close co-operation exists concerning the UKP Lab (Prof. Dr. Iryna Gurevych), and research groups focusing text and data mining as well as partners from digital humanities projects at Darmstadt and at national levels (DARIAH-DE, CLARIN and LOEWE priority “Digital Humanities“ in the state of Hesse).
 
−
 
 
−
We invite excellently qualified postgraduates or excellent graduates from relevant study courses to apply (Computer Science, Computational Linguistics or related subjects).
 
−
 
 
−
Owing to the duration of the project, a contract will be signed for three years. TU Darmstadt offers an opportunity for further scientific qualification (i.e. doctoral degree, habilitation). The salary complies with TV-H (public service labour agreement in the state of Hesse). Applicants will principally be able to work part-time.
 
−
 
 
−
* Tarifvertrag für den öffentlichen Dienst des Landes Hessen (labour agreement for public service in the federal state of Hesse)
 
−
 
 
−
'''Requirements:'''
 
−
 
 
−
* Doctoral degree or diploma/master degree in Computer Science, Computational Linguistics or other relevant subjects;
 
−
* Preferably very good programming skills in Java and Web technologies; knowledge of UIMA;
 
−
* Very good English language skills (written and spoken) and at least basic knowledge of German;
 
−
* Ability to work independently, commitment to the task, the ability to work and communicate in a team and readiness to co-operate;
 
−
 
 
−
Experience in automated language processing, text mining or digital humanities is preferred.
 
−
 
 
−
Women are expressly invited to submit their application. According to the pursuant legal requirements, applicants with disabilities will be preferably treated in the appointment procedure.
 
−
 
 
−
 
 
−
'''How to apply:'''
 
−
 
 
−
Candidates are requested to submit their application in electronic form (including CV and information regarding scientific work experience, university and work reports/references including electronic versions of the thesis and/or three key publications as well as names of two references), quoting the reference code (Referenz-Nr. IZB 2014-02). Please e-mail by February 14, 2014 to Prof. Dr. Iryna Gurevych, German Institute for International Educational Research (DIPF), Postfach 900270, 60442 Frankfurt am Main, Germany, i.e. office-ukp (at) dipf (dot) de. If you have any further questions, please contact Prof. Gurevych by e-mail: gurevych (at) dipf (dot) de.
 
−
 
 
−
 
 
−
 
 
−
== Research Scientist in scientific coordination and transfer in computer science, knowledge and language processing, German Institute for International Educational Research (DIPF), Frankfurt am Main ==
 
−
 
 
−
* Employer: The German Institute for International Educational Research (DIPF)
 
−
* Title: Research Scientist
 
−
* Specialty: scientific coordination and transfer in computer science, knowledge and language processing
 
−
* Location: Frankfurt am Main, Germany
 
−
* Deadline: February 14, 2014
 
−
* Date Posted: January 13, 2014
 
−
* Contact email: gurevych (at) dipf (dot) de
 
−
 
 
−
'''Information about the institute:'''
 
−
 
 
−
The German Institute for International Educational Research (DIPF) (http://www.dipf.de/) n Frankfurt am Main, Germany, is a member of the Gottfried Wilhelm Leibniz Association of Sciences. As a national centre for educational research and educational information, it is jointly funded by the federal government (Bund) and the states (Länder).
 
−
 
 
−
As a scientific institution and member of the Leibniz Association, DIPF targets high-quality fundamental research as well as a research-based development of innovative scientific services. It addresses education as a public domain with high effectiveness and high importance. In relevant national rankings, the Computer Science department at TU Darmstadt regularly holds top positions. Its unique character is marked by excellent competencies in the fields of knowledge discovery on the web focusing on semantic language technology: text mining and information retrieval. By bringing competencies together, DIPF - with Computer Science at TU Darmstadt - has set up an institutional priority domain on knowledge processing and computer science in education.
 
−
 
 
−
'''Job Description:'''
 
−
 
 
−
At DIPF, the Information Center for Education (located in Frankfurt am Main) is looking for a
 
−
 
 
−
* Research Scientist (two-year contract, full time, EG13 TV-H*)
 
−
 
 
−
for tasks in the field of scientific coordination and transfer in computer science, knowledge and language processing.
 
−
 
 
−
 
 
−
The position concerns scientific coordination and transfer tasks in the context of the postgraduate programme Knowledge Discovery in Scientific Literature (http://www.kdsl.tu-darmstadt.de/), founded in 2013  at DIPF and TU Darmstadt, focusing on computational linguistics and language technology. It is nested in the research priority of “computer science for educational research”, newly established at the Information Centre for Education.  The successful candidate will collaborate closely with the Computer Science Department (Prof. Dr. Iryna Gurevych) at Technical University Darmstadt; the position is at the core of the newly established institutional focus on knowledge processing (http://www.werc.tu-darmstadt.de/) at DIPF and Technical University Darmstadt.
 
−
 
 
−
The successful candidate will be expected to coordinate research in the study and qualification programme of the postgraduate programme, monitor the postgraduate programme and its five students and contribute to the transfer of technology. Furthermore, we expect the successful candidate to actively engage in defining requirements, coordinating the assessment of needs and conducting user workshops.
 
−
 
 
−
The position functions as an interface between research on automated analysis of research literature on the one hand and information services respectively information technologies at DIPF on the other. We aim to adapt innovative methods in computer science, language technology and information management to the educational researchers’ needs. These activities target novel means of access to digital science literature and on the web.
 
−
We welcome applications from excellently qualified postdoctoral candidates and (in exceptional cases) excellent graduates striving for further qualification in a scientific-technological field and in research management. 
 
−
 
 
−
A contract will initially be signed for two years. TU Darmstadt offers an opportunity for further scientific qualification (i.e. doctoral degree, habilitation). The salary complies with TV-H (public service labour agreement in the state of Hesse). Applicants will principally be able to work part-time.
 
−
 
 
−
* Tarifvertrag für den öffentlichen Dienst des Landes Hessen (labour agreement for public service in the federal state of Hesse)
 
−
 
 
−
 
 
−
'''Requirements:'''
 
−
 
 
−
- A very good or excellent doctoral degree or likewise excellent diploma/masters degree in computer science, computational linguistics or a related subject domain;
 
−
- Very good English language skills (written and spoken) and at least basic skills in German;
 
−
- Ability to work independently, commitment to the task, the ability to work and communicate in a team and readiness to cooperate;
 
−
- Experience in coordinating distributed software development and its Integration;
 
−
- Experience in conceptualising and conducting events for scientists, users, and the public.
 
−
- Preferably experience in information and text processing, machine learning, very good Java programming skills and knowledge of UIMA, experience with larger-scale software projects.
 
−
 
 
−
Candidates are expected to provide certification of their experience in scientific publishing, acquisition of external funding and project management.
 
  
−
Women are expressly invited to submit their application. According to the pursuant legal requirements, applicants with disabilities will be preferably treated in the appointment procedure.  
+
'''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.
  
−
'''How to apply:'''
+
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.
  
−
Candidates are requested to submit their application in electronic form (including CV and information regarding scientific work experience, university and work reports/references including electronic versions of the thesis and/or three key publications as well as names of two references), quoting the reference code (Referenz-Nr. IZB 2014-01). Please e-mail by February 14, 2014 to Prof. Dr. Iryna Gurevych, German Institute for International Educational Research (DIPF), Postfach 900270, 60442 Frankfurt am Main, Germany, i.e. office-ukp (at) dipf (dot) de. If you have any further questions, please contact Prof. Gurevych by e-mail: gurevych (at) dipf (dot) de.
+
'''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.
  
 +
'''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.
  
−
== Tenure-track Faculty Positions in Natural Language Processing, Institute of Information Science, Academia Sinica, Taipei, Taiwan ==
+
'''Application:'''
 +
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.
  
−
* Employer: Institute of Information Science, Academia Sinica
 
−
* Rank or Title: Assistant/Associate/Full Research Fellow
 
−
* Specialty: Chinese Natural Language Processing and Knowledge Representation
 
−
* Location: Taipei, Taiwan
 
−
* Deadline: Open until filled
 
−
* Date Posted: January 7, 2014
 
−
* Contact email: recruit@iis.sinica.edu.tw
 
  
−
'''Job Description:'''
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
  
−
The Institute of Information Science (IIS) at Academia Sinica, Taiwan invites all qualified candidates to apply for the positions of junior and senior research fellows of all ranks (equivalent to the ranks of tenure track assistant, associate and full professors in a regular academic department without teaching responsibility) in Chinese natural language processing and knowledge representation. Research on Chinese semantic analysis and parsing is particularly emphasized. Exceptional candidates in all areas of Computer Science are also encouraged to apply.
+
* 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]
  
−
Academia Sinica is a national academic research institution in Taiwan that conducts research on a broad spectrum of subjects in science and humanities. IIS is committed to high quality research in computer and information science and engineering. In addition to internal research funding supported by Academia Sinica, external funding through government agencies and industry-sponsored institutions is also available. Starting from 2014, we shall launch an International Ph. D. Program in Social Networks and Human-Centered Computing in collaboration with universities.
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
  
−
Full-time research fellows are free to set their own research directions. IIS currently has about 40 full-time research fellows and close to 300 full-time post doctoral fellows and research assistants. The areas of current research include Systems Technology, Bioinformatics, Multimedia, Data Mining, Natural Language Processing, Network, Theory, and Programming Language.
+
'''Associate Research Scientist'''<br />
 +
'''(PostDoc- or PhD-level; for an initial term of two years)'''
  
−
For additional information about IIS, please visit http://www.iis.sinica.edu.tw
+
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.
  
−
'''Required Qualifications:'''
+
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.
  
−
All Candidates should have a Ph.D. degree in computer science or closely related fields with a strong research and publication record. Senior candidates must demonstrate strong leadership, and have an international reputation evidenced by publications, patents, industrial experiences, or other academic and scholarly achievements. Salary is commensurate with qualifications.
+
* 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.  
  
−
Fluency in Chinese is an advantage, but not required.
+
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.
  
−
'''How to Apply:'''
+
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.
  
−
All candidates should send detailed curriculum vitae, and at least three letters of recommendation to
+
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
−
Dr. Wen-Lian Hsu, Director
+
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.
  
−
Institute of Information Science
+
==  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
  
−
Academia Sinica
+
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.
  
−
Nankang 115, Taipei, Taiwan
+
==  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
  
−
TEL: 886-2-2788-3799ext.1804
+
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.  
  
−
FAX:886-2-2782-4814
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
  
−
E-mail: recruit@iis.sinica.edu.tw
+
'''Essential criteria'''
  
−
== Computational Postdoc position, Johns Hopkins University, Cognitive Science ==
+
* 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.
  
−
* Employer: Johns Hopkins University
+
'''Background about the university'''
−
* Rank or Title: Postdoctoral Fellow
 
−
* Specialty: Computational Linguistics/Cognitive Science
 
−
* Location: Baltimore, MD, USA
 
−
* Deadline: February 17, 2014 or until filled
 
−
* Date Posted: January 7, 2014
 
−
* Contact email: INSPIREpostdoc@jhu.edu
 
  
−
'''Brief Job Description:'''
+
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.
  
−
Applications are invited for a postdoctoral position in the department of Cognitive Science at Johns Hopkins University.
+
'''Background about the project'''
  
−
The appointee will play a central role in a recently-founded group project devoted to developing a novel type of computing that fuses neural network and symbolic computation. In this “Gradient Symbolic Computation“, data consists of discrete structures built of symbols that have continuous activation values. The project addresses human syntax and semantics.
+
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.  
  
−
Keywords: computational linguistics, neural network modeling, syntactic processing, vector-space semantics
+
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.
  
−
'''Detailed Job Description:'''
+
'''More information'''
  
−
The project is funded by NSF’s new INSPIRE program, created to support unusually forward-looking, high-risk/high-return research. The position offers the appointee the opportunity to be a key player in the exciting intellectual environment of a highly interdisciplinary research team of leading faculty members collaborating intensively to break new ground at the foundations of computation and cognition. These faculty members are committed to contributing to the career development of the appointee, who will also have opportunities to pursue their own research projects and to gain experience in teaching. The faculty co-investigators consist of 6 professors from the Cognitive Science and Computer Science Departments at Johns Hopkins (those listed in http://www.nsf.gov/awardsearch/showAward?AWD_ID=1344269 plus Prof. C. Wilson) as well as Prof. M. Goldrick in the Linguistics Department at Northwestern.
+
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.
  
−
The ideal appointee will conduct development and extensive testing of:
+
==  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
  
−
* general-purpose software to support symbolic-level computation over gradient symbol structures
+
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.
  
−
* general-purpose software for simulating neural network implementations of this gradient symbolic computation
+
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. 
  
−
* new machine-learning algorithms, including deep compositional networks
+
'''Skills'''
  
−
* new theories of compositional vector-space semantics and new neural-network architectures for implementing them
+
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.
  
−
* new psycholinguistic models of human syntactic production and comprehension processes
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
−
Most critical is the work on general-purpose software. This work will be conducted in close collaboration with faculty whose expertise spans all project areas. Johns Hopkins is a world leader in computational approaches to language science and engineering.
+
'''Research Team'''
  
−
The initial appointment is for one year, with an expectation of a second year, conditioned on satisfactory progress. Starting date is August 1, 2014.
+
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”.
  
−
'''How to Apply:'''
+
Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).
  
−
Applications will be processed until the position is filled. For full consideration, applications and letters should be received by February 17, 2014. An application consists of a single PDF file including (i) a cover letter detailing the applicant’s interests in connection with the project, the qualifications they bring to the work, and the training they would like to receive from the position; (ii) a current CV; (iii) a document containing links to their relevant publications (ideally, integrated into the CV); (iv) a research statement describing their past, on-going, and planned future work; and (v) (optional) a statement concerning their teaching experience and interests. The application, along with three letters of recommendation, must be emailed to INSPIREpostdoc@jhu.edu. Please ensure that your name is in the Subject line of all materials that you AND your References submit.
+
Deadline of applications: 13/03/2017
  
−
Johns Hopkins University is an Equal Opportunity, Affirmative Action employer; minorities, women, Vietnam-era veterans, disabled veterans and individuals with disabilities are encouraged to apply.
+
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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