University of Copenhagen

Postdocs in Natural Language Processing (BB-7D156)

Found in: Neuvoo DK

Description:

Natural Language Processing Section
Department of Computer Science
Faculty of Science

University of Copenhagen

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering two postdoc positions in Natural Language Processing commencing on 1 September 2021.

Description of the scientific environment

The Natural Language Processing Section provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing, natural language understanding, computational linguistics and multi-modal language processing. It is housed within the main Science Campus, which is centrally located in Copenhagen. The section came into effect on 1 January 2021 as a spin-off from the Machine Learning section, to which it still maintains close ties. Further information about research at the Department is available here: https://di.ku.dk/english/research/. The successful candidates will join Isabelle Augenstein’s Natural Language Understanding research group (www.copenlu.com/). The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked 2nd in Europe according to CSRankings.

Project descriptions

Project 1

The first postdoc position is offered in the context of a DFF Sapere Aude research leader fellowship on ‘Learning to Explain Attitudes on Social Media (EXPANSE) held by Isabelle Augenstein. Sapere Aude is a program by the Independent Research Fund Denmark to support the most talented younger researchers in Denmark with funding for blue-skies research to build up or expand their research groups.

The EXPANSE project studies attitudes voiced on social media, examining what is said, and explaining it by examining why, how and by whom attitudes are stated. Currently, the only criterion commonly taken into account when researching and developing not just such stance detection, but Natural Language Processing models in general, is predictive performance, e.g. how well models can predict labels such as ‘positive’, ‘negative’ or ‘neutral’. This does not provide any insights into why and how models arrive at certain predictions, which is crucial for utilising predictions for decision making. By contrast, this project will examine explainability as a success criterion, in an interdisciplinary approach which combines Natural Language Processing research with sociological theories.

In addition to the principle investigator and the postdoc, the project team will also include two PhD students, as well as interdisciplinary collaborators from sociology.
More information about the project can also be found at: https://dff.dk/en/grants/research-leaders-2020/researchleader-14

The ideal candidate for the first postdoc position would have a background in Computational Social Science as well as Natural Language Processing, prior experience in inter-disciplinary collaborations, and a passion for blue-skies research.


Project 2
The second postdoc position is offered in the context of an inter-disciplinary project involving the Centre for Digital Education at the University of Copenhagen, the Natural Language Processing research group, as well as a market leader in educational technologies.
The postdoc would research explainable relation extraction as well as question answering methods to automatically analyse and provide feedback on student essays.
A signed grant agreement, which is a pre-condition of employment, is still pending at the time of advertising this position, and is expected to be in place at the very latest by the time interviews are held, which also means more details about this project can only be shared then.

The ideal candidate for the second postdoc position would have a background in NLP for educational applications, explainable AI and/or information extraction, and prior experience in inter-disciplinary collaborations, also involving industry partners.

Job description

There are two positions available, for a 2.5 year period (postdoc 1) and a 2 year period (postdoc 2), respectively, with a preferred start date of 1 September 2021, though potentially also earlier upon request.

The key tasks of a postdoc are:

  • To plan and carry out research with increasing autonomy
  • To write scientific articles
  • To disseminate research nationally and internationally
  • To collaborate with researchers both within the research group, and with external project partners
  • To assist in teaching if requested, typically by co-supervising BSc and MSc students or by giving guest lectures in MSc courses

  • The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates.

    Enquiries about the positions can be made to Isabelle Augenstein augenstein@di.ku.dk, Associate Professor and head of the NLP section at the Department of Computer Science.

    Formal requirements
    Applicants should hold a PhD degree in Computer Science, Computational Social Science or a related field, and have good written and oral English skills. The assessment of your qualifications will also be made based on previous scientific publications and relevant work experience.

    Terms of employment

    The position is covered by the Memorandum on Job Structure for Academic Staff.

    Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

    The starting salary is currently up to DKK 437.843 including annual supplement (+ pension up to DKK 74.871). Negotiation for salary supplement is possible.

    The application, in English, must be submitted electronically by clicking APPLY NOW below.

    Please include

  • Curriculum vitae
  • Diplomas (Master and PhD degree or equivalent)
  • Cover letter, explaining your interest in the advertised positions
  • Complete publication list
  • Separate reprints of 3 particularly relevant papers
  • calendar_today1 day ago

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