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== Funded PhD Position in NLP & Music Technology, Universitat Pompeu Fabra, Barcelona, Spain ==
  
== Research Director NLP and Speech Processing / Educational Testing Service / Princeton, New Jersey ==
+
* 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: 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:'''
+
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 .
  
ETS (Educational Testing Service), with headquarters in Princeton, NJ, is a global $1.3B not for profit organization. Our mission is to advance quality and equity in education by providing fair and valid assessments, performing educational research and influencing policies that promote learning, performance, education and professional development.
 
 
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:'''
 
  
To qualify, you must possess:
 
* 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:'''
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== Scientific System Developer, UKP Lab, TU Darmstadt ==
  
Please apply online at: http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=160741&BUID=2538
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* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
 +
* Title: Scientific System Developer
 +
* Specialty: Argument Mining, Machine Learning, Big Data Analysis
 +
* Location: Darmstadt
 +
* Deadline: May 31, 2017
 +
* Date posted: May 3, 2017
 +
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de]
  
'''Information about the institute:'''
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The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has an opening for a
  
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.
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'''Scientific System Developer'''<br>
 +
'''(PostDoc- or PhD-level; time-limited project position until April 2020)'''
  
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
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to strengthen the group’s profile in the area of Argument Mining, Machine Learning and Big Data Analysis. The UKP Lab is a research group comprising over 30 team members who work on various aspects of Natural Language Processing (NLP), of which Argument Mining is one of the rapidly developing focus areas in collaboration with industrial partners.  
  
 +
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.
  
== Research Intern in Natural Language Processing (NLP) / Text Mining / Digital Humanities ==
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UKP’s wide cooperation network both within its own research community and with partners from industry provides an excellent environment for the position to be filled. The Department of Computer Science of TU Darmstadt is regularly ranked among the top ones in respective rankings of German universities. Its unique and recently established Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES) funded by the DFG emphasizes NLP, text mining, machine learning, as well as scalable infrastructures for the assessment and aggregation of knowledge. UKP Lab is a highly dynamic research group committed to high-quality research results, technologies of the highest industrial standards, cooperative work style and close interaction of team members working on common goals.
  
* Employer: The Ubiquitous Knowledge Processing Lab (UKP Lab) in Darmstadt/Frankfurt
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Applications should include a detailed CV, a motivation letter and an outline of previous working or research experience (if available).
* 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:'''
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Applications from women are particularly encouraged. All other things being equal, candidates with disabilities will be given preference. Please send the application to: [mailto:jobs@ukp.informatik.tu-darmstadt.de jobs@ukp.informatik.tu-darmstadt.de] by 31.05.2017. The position is open until filled. Later applications may be considered if the position is still open.
  
The Ubiquitous Knowledge Processing Lab (UKP Lab) offers several exciting internship opportunities in cutting-edge research projects as
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Questions about the position can be directed to: [mailto:jobs@ukp.informatik.tu-darmstadt.de Johannes Daxenberger]; phone: [+49] (0)6151 16-25297
 +
We look forward to receiving your application!
  
* 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)
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== Two postdoc positions on plausible reasoning with vector space embeddings at Cardiff University ==
  
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.  
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* 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]
  
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.  
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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.  
  
'''Requirements:'''
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Successful candidates are expected to have a strong background in natural language processing, machine learning, or knowledge representation. This research will be part of Steven Schockaert's FLEXILOG project, which is funded by the European Research Council (ERC)
  
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.  
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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.  
  
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.
 
  
 +
'''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.
  
'''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.
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== Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis, University of Colorado Boulder ==
  
 +
* Employer: University of Colorado Boulder
 +
* Title: Postdoctoral Research Associate
 +
* Specialty: Advanced Machine Learning
 +
* Location: Boulder, Colorado, United States
 +
* Deadline: Ongoing, desired start Summer/Fall 2017
 +
* Date posted: March 31, 2017
 +
* Contact: [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
'''Information about the institute:'''
+
'''Postdoc in Machine Learning for Multimodal Behavior and Mental State Analysis''' <br/>
 +
(Institute of Cognitive Science and Department of Computer Science at the University of Colorado Boulder)
  
The 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.
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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).
  
== Research Scientist for Automated Language Processing / Text Mining / Digital Humanities, German Institute for International Educational Research (DIPF), Frankfurt am Main ==
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The candidate will work under the supervision of Dr. Sidney D’Mello and will play a collaborative and co-leadership role in a vibrant research team encompassing researchers in Computer Science, Cognitive Science, and Education.
  
* Employer: The German Institute for International Educational Research (DIPF)
+
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.
* 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:'''
+
'''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
  
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).
+
'''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
  
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.
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'''Job Details'''
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* 1-2 year position. Initial contract is for one year (providing renewal after 6-month probationary period). Second year contract is based on performance and availability of funds.
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* Start date is negotiable, but anticipated for Summer/Fall 2017.
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* Competitive salary with benefits commensurate with qualifications. This position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.
  
 +
'''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.
  
'''Job Description:'''
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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.
  
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
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The University of Colorado is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, the University of Colorado does not discriminate on the basis of race, color, creed, religion, national origin, sex (including pregnancy), disability, age, veteran status, sexual orientation, gender identity or expression, genetic information, political affiliation or political philosophy in its programs or activities, including employment, admissions, and educational programs. Inquiries may be directed to the Boulder Campus Title IX Coordinator by calling 303-492-2127. In accordance with the Americans with Disabilities Act, alternative formats of this ad can be provided upon request for individuals with disabilities by contacting Human Resources at [mailto:adacoordinator@colorado.edu adacoordinator@colorado.edu].
  
* Research Scientist for Automated Language Processing / Text Mining / Digital Humanities (three-year contract, full time, EG13 TV-H*)
+
'''Questions''' <br/>
 +
Please email [mailto:sidney.dmello@gmail.com Dr. Sidney D’Mello]
  
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.
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== Researcher in Machine Learning and NLP, DFKI, Germany ==
  
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).
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* Employer: [http://www.dfki.de/ DFKI GmbH], Germany
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* Title: Researcher
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* Specialty: Machine Learning and Natural Language Processing, Deep Learning, Machine Translation
 +
* Location: Saarbruecken
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* Deadline: March 31, 2017
 +
* Date posted: March 13, 2017
 +
* Contact: [mailto:mlt-sek@dfki.de Prof. Josef van Genabith]
  
We invite excellently qualified postgraduates or excellent graduates from relevant study courses to apply (Computer Science, Computational Linguistics or related subjects).
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The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning with a focus on Deep Learning, Machine Translation and possibly other areas of NLP. Depending on experience, the position is available at the Junior/Researcher/Senior/Principal Researcher level.
  
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.
+
'''Key research responsibilities''' include:
 +
* machine and deep learning for natural language processing/machine translation
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* software development and integration
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* publication in top-tier conferences and journals
  
* Tarifvertrag für den öffentlichen Dienst des Landes Hessen (labour agreement for public service in the federal state of Hesse)
+
'''General responsibilities''' include:
 +
* engagement with industry partners and contract research
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* identification of funding opportunities and engagement in proposal writing
 +
* contribution to teaching and supervision in accordance with University and DFKI rules and regulations
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* administrative work associated with programmes of research
  
 
'''Requirements:'''
 
'''Requirements:'''
 +
* MSc/PhD in computer science, machine learning, natural language processing, computational linguistics or similar
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* Strong background and track record in machine learning, neural nets and deep learning
 +
* Strong background and track record in NLP and MT - Excellent programming skills
 +
* Excellent problem solving skills, independent and creative thinking
 +
* Excellent team working and communication skills
 +
* Excellent command of written and oral English
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* Command of German and other  languages not a requirement but helpful
  
* Doctoral degree or diploma/master degree in Computer Science, Computational Linguistics or other relevant subjects;
+
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).
* 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.
+
'''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.
  
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.  
+
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.
  
 +
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.
  
'''How to apply:'''
+
'''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.
  
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.
+
'''Starting date, duration, salary:'''
 +
Preferred starting date is May/June 2017. The position is available until June 30, 2020, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills.
  
 +
'''Application:'''
 +
Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) to [mailto:mlt-sek@dfki.de Prof. Josef van Genabith] referring to job opening no. 22/17-JvG. Deadline for applications is March 31st, 2017. The position remains open until filled. Please contact [mailto:josef.van_genabith@dfki.de Prof. van Genabith] for informal inquiries.
  
  
== Research Scientist in scientific coordination and transfer in computer science, knowledge and language processing, German Institute for International Educational Research (DIPF), Frankfurt am Main ==
+
== Associate Research Scientist, UKP Lab, TU Darmstadt ==
  
* Employer: The German Institute for International Educational Research (DIPF)
+
* Employer: [https://www.ukp.tu-darmstadt.de/ UKP Lab], [https://www.informatik.tu-darmstadt.de/ Technische Universität Darmstadt], Germany
* Title: Research Scientist
+
* Title: Associate Research Scientist
* Specialty: scientific coordination and transfer in computer science, knowledge and language processing
+
* Specialty: Interactive Machine Learning (IML) or Natural Language Processing for Language Learning
* Location: Frankfurt am Main, Germany
+
* Location: Darmstadt
* Deadline: February 14, 2014
+
* Deadline: March 8, 2017
* Date Posted: January 13, 2014
+
* Date posted: February 21, 2017
* Contact email: gurevych (at) dipf (dot) de
+
* Contact: [mailto:jobs@ukp.informatik.tu-darmstadt.de Prof. Iryna Gurevych]
  
'''Information about the institute:'''
+
The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technische Universität (TU) Darmstadt, Germany has two openings for an
  
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).
+
'''Associate Research Scientist'''<br />
 +
'''(PostDoc- or PhD-level; for an initial term of two years)'''
  
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.
+
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.
  
'''Job Description:'''
+
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.
  
At DIPF, the Information Center for Education (located in Frankfurt am Main) is looking for a
+
* 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.
  
* Research Scientist (two-year contract, full time, EG13 TV-H*)
+
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.
  
for tasks in the field of scientific coordination and transfer in computer science, knowledge and language processing.
+
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.
  
 +
Applications should include a detailed CV, a motivation letter and an
 +
outline of previous working or research experience (if available).
  
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.
+
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.
  
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.
+
==  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 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.
+
The Department of Linguistics at Northwestern University invites applications for a full-time, non-renewable, two year postdoctoral fellowship in any area of linguistics. We are looking for candidates who pursue an integrated, interdisciplinary approach to the scientific study of language, utilizing experimental methods, corpus analysis, and/or computational modeling to inform linguistic theory and its applications. The fellowship period begins September 1, 2017. Each year, the fellow will be expected to teach one undergraduate-level course in the Department of Linguistics. The fellow will also serve as an undergraduate adviser for the Cognitive Science Program, working with students pursuing the major and minor on academic issues (e.g., course selection, research opportunities, progress on degree requirements).
We 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.
+
 
+
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.
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.
+
 
+
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.
* 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.
 
 
 
 
 
'''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 2014-01). 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.
 
 
 
 
 
== Tenure-track Faculty Positions in Natural Language Processing, Institute of Information Science, Academia Sinica, Taipei, Taiwan ==
 
 
 
* 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:'''
 
 
 
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.
 
 
 
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.
 
 
 
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.
 
 
 
For additional information about IIS, please visit http://www.iis.sinica.edu.tw
 
 
 
'''Required Qualifications:'''
 
 
 
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.
 
 
 
Fluency in Chinese is an advantage, but not required.
 
 
 
'''How to Apply:'''
 
 
 
All candidates should send detailed curriculum vitae, and at least three letters of recommendation to
 
 
 
Dr. Wen-Lian Hsu, Director
 
 
 
Institute of Information Science
 
 
 
Academia Sinica
 
 
 
Nankang 115, Taipei, Taiwan
 
 
 
TEL: 886-2-2788-3799ext.1804
 
 
 
FAX:886-2-2782-4814
 
 
 
E-mail: recruit@iis.sinica.edu.tw
 
 
 
== Computational Postdoc position, Johns Hopkins University, Cognitive Science ==
 
 
 
* Employer: Johns Hopkins 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:'''
 
 
 
Applications are invited for a postdoctoral position in the department of Cognitive Science at Johns Hopkins University.
 
 
 
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.
 
 
 
Keywords: computational linguistics, neural network modeling, syntactic processing, vector-space semantics
 
 
 
'''Detailed Job Description:'''
 
 
 
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.
 
 
 
The ideal appointee will conduct development and extensive testing of:
 
 
 
* general-purpose software to support symbolic-level computation over gradient symbol structures
 
 
 
* general-purpose software for simulating neural network implementations of this gradient symbolic computation
 
 
 
* new machine-learning algorithms, including deep compositional networks
 
 
 
* new theories of compositional vector-space semantics and new neural-network architectures for implementing them
 
 
 
* new psycholinguistic models of human syntactic production and comprehension processes
 
 
 
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.
 
 
 
The initial appointment is for one year, with an expectation of a second year, conditioned on satisfactory progress. Starting date is August 1, 2014.
 
 
 
'''How to Apply:'''
 
 
 
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.
 
 
 
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.
 
 
 
== Postdoc in Automatic Speech Recognition and Dialog-Centered Natural Language Understanding  ==
 
 
 
* Employer: University of Notre Dame
 
* Rank or Title: Postdoctoral Researcher
 
* Specialty: Speech recognition, Dialogue, Natural Language Understanding
 
* Location: South Bend, Indiana
 
* Deadline: Open until filled
 
* Date Posted: Dec 6, 2013
 
* Contact email: aolney at memphis.edu
 
 
 
'''Brief Job Description:'''
 
 
 
The successful candidate will conduct research in automatic speech recognition and dialog-centered natural language understanding. He/she will participate in the design, development, and exploration of innovative methods, algorithms and techniques that bridge acoustic/language modeling and dialogue-focused natural language understanding on real-world, multi-party speech data collected in educational contexts.
 
 
 
The position is for two years (providing renewal based on Year 1 performance) starting as early as February 1, 2014. Possible extension to a third year based on availability of funds. Start date is negotiable.
 
Competitive salary with benefits commensurate with qualifications.
 
 
 
'''Required Qualifications:'''
 
 
 
* Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field
 
* Research experience in one or more of the following research areas (automatic speech recognition, natural language understanding, or related area of natural language processing)
 
* A solid publication track record in one or more of the aforementioned areas
 
* Ability to work both individually and as a member of an interdisciplinary team
 
* Ability to mentor graduate and undergraduate students
 
 
 
'''How to Apply:'''
 
 
 
Applicants should email (1) cover letter, (2) current CV, and (3) name, title, and contact information of three references to Kristopher Kopp (kristopherkopp at gmail.com). Inquires may be addressed to Sidney D’Mello (sdmello at nd.edu) and Andrew Olney (aolney at memphis.edu).
 
 
 
'''About Us:'''
 
 
 
Further information on the Computer Science department can be found at http://cse.nd.edu/.
 
 
 
== TTS Language Engineer - Arabic, Hebrew, Indonesian, Turkish, Employment Agency contracting for Google, London, UK  ==
 
 
 
* Employer: Employment agency contracting for Google
 
* Rank or Title: TTS Language Engineer (4) positions - Arabic, Hebrew, Indonesian, Turkish
 
* Specialty: TTS, Computational Linguistics
 
* Location: London, UK
 
* Deadline: Open until filled
 
* Date Posted: November 21, 2013; Updated December 17, 2013
 
* Contact email: tts_jobs at google.com
 
 
 
'''Brief Job Description:'''
 
 
 
You will be helping with technical tasks involved in creating a speech
 
synthesiser. This includes:
 
 
   
 
   
1. Developing rules for a text normalisation system;
+
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.
2. Large scale data mining;
 
3. Customising language building tools for either Arabic, Hebrew, Indonesian or Turkish
 
4. TTS quality evaluation
 
 
 
'''Preferred Qualifications:'''
 
 
 
1. Recent CS or Computational Linguistics graduate or closely related
 
discipline
 
2. Native-level speaker of either Arabic, Hebrew, Indonesian or Turkish and fluent in English:
 
3. Proficiency in Unix/Python/C++
 
4. Interest in data mining and natural language processing a plus
 
 
 
'''How to Apply:'''
 
 
 
This is an opportunity to work on cutting edge technology in a dynamic team
 
of world-class experts. This is a temporary position for 9 months, with a
 
possibility of extension. The position is based in London.
 
 
 
For immediate consideration please send your CV and Cover Letter to tts_jobs at google.com
 
 
 
For more information, please contact tts_jobs at google.com
 
 
 
== Postdoctoral Fellow, Bioinformatics Technology Lab, BC Genome Sciences Centre  ==
 
 
 
* Employer: British Columbia Cancer Agency
 
* Rank or Title: Postdoctoral Fellow
 
* Specialty: natural language processing, machine learning
 
* Location: Vancouver, BC, Canada
 
* Deadline: Open until filled
 
* Date Posted: November 18, 2013
 
* Contact email:  bcgscjobs@bcgsc.ca
 
 
 
'''Brief 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 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 machine learning tools for automated literature survey
 
 
 
• Analysis and annotation of data from genome and transcriptome sequencing projects
 
 
 
• 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
 
 
 
Work may also involve travel to the research and development labs of a US corporation, not to exceed three months a year.
 
 
 
'''Required Qualifications:'''
 
 
 
The ideal candidate should possess a PhD degree and recent proven experience in bioinformatics or computer science. A strong publication record in the field, and demonstrated technical writing skills are highly desirable.
 
 
 
'''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 13-11-01") 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
 
 
 
== Graduate Studentship, Bioinformatics Technology Lab, BC Genome Sciences Centre  ==
 
 
 
* Employer: British Columbia Cancer Agency
 
* Rank or Title: Graduate Student
 
* Specialty: natural language processing, machine learning
 
* Location: Vancouver, BC, Canada
 
* Deadline: Open until filled
 
* Date Posted: November 18, 2013
 
* Contact email:  ibirol@bcgsc.ca
 
 
 
'''Brief Description:'''
 
 
 
Bioinformatics Technology Lab at the Genome Sciences Centre is seeking graduate students at the Masters and PhD levels.
 
Under the supervision of Dr. Inanc Birol, students will work with other trainees and research scientists in a group environment to develop cutting-edge bioinformatics technologies for high throughput sequence analysis, de novo assembly, clinical genomics, big data visualization, and automated literature search and interpretation.
 
 
 
'''Required Qualifications:'''
 
 
 
If you have any combination of the following skills, and a passion to apply them at a state-of-the-art genome centre, we would be interested in you.
 
 
 
• Sophisticated programming skills (C++ and Python preferred)
 
 
 
• Parallel computation expertise (MPI or MP)
 
 
 
• Strong natural language processing background (familiarity with argumentation frameworks an asset)
 
 
 
• Experience with de novo assembly tools (ABySS and Trans-ABySS preferred)
 
 
 
• Graph theory background
 
 
 
• Database development and administration experience (PostgreSQL or MySQL)
 
 
 
'''How to Apply:'''
 
 
 
Please send your cover letter, CV and transcripts to ibirol@bcgsc.ca
 
 
 
Successful students will be registered at either CIHR’s Bioinformatics Training Program or Medical Genetics Graduate Program at the University of British Columbia.
 
 
 
'''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 job available in neural decoding of language, University of Rochester ==
 
 
 
* Employer: University of Rochester
 
* Rank or Title: Postdoctoral Research Fellow
 
* Specialty: Models of semantic composition, semantic similarity, machine learning
 
* Location: Rochester, NY, USA
 
* Deadline: Open until filled
 
* Date Posted: November 7, 2013
 
* Contact email: rajeev dot raizada at gmail dot com
 
 
 
'''Brief Job Description:'''
 
 
 
A postdoctoral position is available in the Department of Brain & Cognitive Sciences at the University of Rochester in the lab of Rajeev Raizada (http://raizadalab.org).
 
 
 
The position will concentrate on the neural decoding of language, in particular the semantic representation of words embedded in sentences. Experience in some or all of the following areas would be ideal: computational linguistics (especially models of the semantic composition of multiple words into phrases and sentences), natural language processing, multivoxel pattern-based fMRI analysis, machine learning (especially kernels or similarity-based approaches). Experience with Matlab or some other scientific programming language (e.g. SciPy, R) is required.
 
 
 
'''Required Qualifications:'''
 
 
 
Applicants must have a PhD in linguistics, psychology, computer science, neuroscience or a related field. Salary will be on the standard NIH postdoc payscale. The position is available immediately and has funding for a two year period, although it could potentially be extended beyond that time if mutually agreed and if additional funding is obtained.
 
 
 
'''How to apply:'''
 
 
 
To apply, please send a description of your research interests, a CV, the names of three referees, and weblinks to representative publications to rajeev dot raizada at gmail dot com. Large files such as PDFs of papers should be sent as weblinks (e.g. to your publications webpage, or using Dropbox) rather than as e.mail attachments. Interviews can be conducted via Skype.
 
 
 
'''Information about the university and the department'''
 
 
 
The Department of Brain & Cognitive Sciences at the University of Rochester (http://www.bcs.rochester.edu) has a strong focus on computational and statistical studies of neural representations, and has researchers working in language, vision, computation, development and neuroimaging. The Rochester Center for Brain Imaging (http://rcbi.rochester.edu) has a research-dedicated 3T Siemens Trio scanner.
 
 
 
== Post-doctoral Research Fellow - Nanyang Technological University, Singapore ==
 
 
 
* Employer: Nanyang Technological University
 
* Rank or Title: Post-doctoral Research Fellow
 
* Specialty: Natural Language Processing, Semantic Web
 
* Location: Singapore
 
* Deadline: Will be open until filled
 
* Date Posted: November 2, 2013
 
* Contact email: jungjae.kim@ntu.edu.sg
 
 
 
'''Brief Job Description:'''
 
 
 
The Natural Language Processing group in the School of Computer Engineering, Nanyang Technological University, Singapore has an opening for a post-doctoral researcher in the areas of ontology engineering and text mining, funded by Rolls-Royce@NTU Corporate Laboratory.
 
 
 
The position involves applying scientific, technical and software engineering skills to conduct research on ontology learning, ontological annotation on informal text, and semantic indexing and search and the development of prototypes demonstrating the successful application of the research.
 
 
 
'''Required Qualifications:'''
 
 
 
A Ph. D. in Computational Linguistics, Computer Science, or a related discipline with specialization in text mining and/or ontology engineering. Independent research experiences and experiences in developing and deploying text mining and/or ontology engineering technology capabilities in an academic or industrial environment are expected.
 
  
'''How to apply:'''
+
==  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
  
Please send a copy of your resume, along with a cover letter, to Jung-jae Kim <jungjae.kim@ntu.edu.sg>
+
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.  
  
==  Assistant Professor Position - Computational Linguistics/Language Science - Rochester Institute of Technology ==
+
This research will be part of the FLEXILOG project, which is funded by the European Research Council (ERC)
  
* Employer: Rochester Institute of Technology
+
'''Essential criteria'''
* Rank or Title: Assistant Professor
 
* Specialty: Computational Linguistics/Language Science
 
* Location: Rochester, NY, USA
 
* Deadline: Review of applications will begin on November 25, 2013
 
* Date Posted: October 11, 2013
 
* Contact email: coagla@rit.edu
 
  
'''Brief Job Description:'''
+
* 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.
  
The Department of English at the Rochester Institute of Technology invites applications for an Assistant Professor of English tenure-track position to begin August 13, 2014 with specialization in computational linguistics and/or innovative technical methods in language science, with a focus on one or more areas of application. Possible areas include:
+
'''Background about the university'''
  
* Cultural or social analytics
+
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.
* Speech technology
 
* Human-computer communication
 
* Clinical, assistive, and/or access technology
 
* Cognitive modeling of linguistic processes (for example reading)
 
* Games and/or social media
 
  
The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on curricular and research initiatives in digital humanities and language science.
+
'''Background about the project'''
  
'''Detailed Job Description:'''
+
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 successful applicant will be a teacher and a researcher with an agenda that emphasizes innovative technical methods in linguistics, for instance natural language processing, corpus-based studies, linguistic/multimodal sensors, speech technology, and/or other computational approaches. We are seeking a scholar who engages in disciplinary and interdisciplinary teamwork and has a coherent plan for grant seeking activities. The right candidate will contribute to our department’s profile in the digital humanities, in addition to furthering our interdisciplinary language science curriculum in a college of liberal arts at a technical university. Contributions that build students’ global education experiences are additionally valued.
+
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.
  
Teaching assignments may include Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Advanced Topics in Computational Linguistics, Language & Brain, self-designed courses, and other courses in the linguistics or general education frameworks such as Dialects & Identity, Text & Code, or Evolving English Language. The course teaching load is 3/2.
+
'''More information'''
  
We are seeking an individual who has the ability and interest in contributing to a community committed to Student Centeredness; Professional Development and Scholarship; Integrity and Ethics; Respect, Diversity and Pluralism; Innovation and Flexibility; and Teamwork and Collaboration. Select to view links to RIT’s [http://www.rit.edu/~w-policy/sectionA/corevalues.html core values], [http://www.rit.edu/studentaffairs/studentconduct/RITHonorCode1.htm honor code], and [http://finweb.rit.edu/humanresources/diversity/commitment.html diversity commitment].  
+
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 University and Rochester Community:'''
+
==  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
  
RIT is a national leader in professional and career-oriented education. Talented, ambitious, and creative students of all cultures and backgrounds from all 50 states and more than 100 countries have chosen to attend RIT.  Founded in 1829, Rochester Institute of Technology is a privately endowed, coeducational university with nine colleges and institutes emphasizing career education and experiential learning. With approximately 15,000 undergraduates and 3,000 graduate students, RIT is one of the largest private universities in the nation. RIT offers a rich array of degree programs in engineering, science, business, and the arts, and is home to the National Technical Institute for the Deaf. RIT has been honored by ''The Chronicle of Higher Education'' as a "Great Colleges to Work For" for four years. RIT is responsive to the needs of dual career couples by our membership in the [http://www.upstatenyherc.org/home/index.cfm?site_id=671 Upstate NY HERC].
+
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.
  
Rochester, located on Lake Ontario, is the 79<sup>th</sup> largest city in the United States and the third largest city in New York State. The Greater Rochester region, which is home to nearly one million people, is rich in cultural and ethnic diversity, with a population comprised of approximately 16% African and Latin Americans and another 7% of international origin. It is also home to the largest deaf community per capita in the U.SRochester ranks 3<sup>rd</sup> best metropolitan regions for Raising a Family" by ''Forbes Magazine''; 6<sup>th</sup> among 379 metropolitan areas as "Best Places to Live in America" by ''Places Rated Almanac''; 1<sup>st</sup> in ''Expansion Management Magazine''’s ranking of metropolitan areas having the best “Quality of Life in the Nation”; and is among ''Essence Magazine''’s "Top 10 Cities for Black Families."
+
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.   
  
'''Required Minimum Qualifications:'''
+
'''Skills'''
  
* Ph.D. in Linguistics (or an allied field) in hand prior to appointment date
+
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.  
* Advanced graduate coursework in language science and technical methods
 
* Evidence of outstanding teaching
 
* Experience teaching or mentoring diverse or multi-disciplinary students
 
* Evidence of publication and a coherent plan for research and grant seeking activities
 
* Ability to contribute in meaningful ways to the college’s continuing commitment to cultural diversity, pluralism, and individual differences.
 
  
'''How to Apply:'''
+
* Duration of post: Immediately until 31st October 2018
 +
* Salary: £31,076-£38,183 per annum
  
Apply online at [http://careers.rit.edu/faculty http://careers.rit.edu/faculty]. Search: 797BR. Please submit your cover letter; CV; copy of transcripts of graduate coursework; a research statement; a teaching statement; writing sample/portfolio; [https://www.rit.edu/academicaffairs/facultyrecruitment/forms/Diversity_Statement_Guide_for_candidates_4-12.docx Contribution to Diversity Statement]; and the names, addresses and phone numbers for three references.
+
'''Research Team'''
  
'''Contact:'''
+
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”.
  
Please direct questions to Dr. Cecilia Ovesdotter Alm at: <coagla@rit.edu> or (585) 475-7327.
+
Informal enquiries:  Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).  
  
'''Application Deadline:'''
+
Deadline of applications: 13/03/2017
  
Review of applications will begin on: November 25, 2013.
+
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