Ledig stilling på Universitetet i Oslo

Blindern og Urbygningen (Foto: Wikimedia og Colourbox)

PhD Research Fellow in Natural Language Processing

Deadline: 28.02.2023

Universitetet i Oslo

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.


The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics.


The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees, about 280 of these in full time positions. The full time tenured academic staff is 75, mostly Full/Associate Professors.

Job description

Position as PhD Research Fellow in Natural Language Processing (NLP) available at the Language Technology Group (LTG) within the Section for Machine Learning at the Department of Informatics, University of Oslo.

The fellowship period is three (3) years, starting no later than August 2023.

A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

More about the position

The focus of this PhD-project is on explainable semantic change detection. Current computational approaches to modeling synchronic and diachronic semantic change achieve considerable success as measured by shared tasks and NLP research papers (Tahmasebi et al., LChange 2022). But they are mostly non-transparent and obscure for historical linguists and lexicographers. One of the reasons is that current methods lack explanatory power. This project is supposed to address this issue. The overall aim is to transform numerical predictions into human-readable interpretations linked to rich linguistic tradition of semantic shift categorization.

Particular paths towards this aim are going to be defined in discussion between the supervisor(s) and the successful applicant.

LTG is an international and diverse group, where current prominent research activities include training and bench-marking large-scale language models, semantic change analysis, semantic parsing, event extraction and sentiment analysis. While the research profile of the group is heavily machine-learning oriented, our projects typically combine data-driven approaches with an interest for linguistic analysis and knowledge. The group has access to excellent high-performance computing infrastructure and actively participates in research collaborations supported by Norwegian and European funding agencies .

For more information about the Language Technology Group (LTG) at IFI, please see here.

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for this fellowship will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

Applicants must:

  • hold a Master’s degree or equivalent in Natural Language Processing, or in Computer Science with a specialization in NLP, see grade requirements below.
  • foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
  • be able to demonstrate broad knowledge of core NLP tasks, especially related to semantics
  • have previous experience with machine learning-based approaches to NLP, including experience with neural architectures
  • possess strong programming skills and implementation experience
  • be fluent in English

Candidates without a Master’s degree have until 30 June, 2023 to complete the final exam.

Grade requirements:

The norm is as follows:

  • the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
  • the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
  • the Master’s thesis must have the grade B or better in the Norwegian educational system
  • Fluent oral and written communication skills in English
  • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

Personal skills

  • Publication track at NLP and computational linguistics venues is a plus
  • Prior experience with lexical semantic change detection task is a big plus
  • Candidates with linguistics background (even if very basic) will be given priority.
  • We seek highly motivated, open-minded, and scientifically curious candidates
  • Candidates should be able to work independently, as well as in a team (with the supervisor or with fellow students)
  • Candidates should have strong written and verbal communication skills

We offer

  • Salary NOK 501 200 – 544 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
  • Attractive welfare benefits and a generous pension agreement
  • Vibrant international academic environment
  • Career development programmes
  • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

  • Cover letter - statement of motivation and research interests
  • CV (summarizing education, positions and academic work - scientific publications)
  • Copies of the original Bachelor and Master’s degree diploma, transcripts of records and
  • Documentation of English proficiency
  • List of publications and academic work that the applicant wishes to be considered by the evaluation committee
  • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job”). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English or a Scandinavian language.

Applicants will be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

For further information please contact Associate Professor Andrey Kutuzov (e-mail: andreku@ifi.uio.no)

For questions regarding Jobbnorge, please contact HR Adviser Therese Ringvold, e-mail: therese.ringvold@mn.uio.no.

Apply for this job

Powered by Labrador CMS