PhD Research Fellow in Natural Language Processing

About the position

Position as PhD Research Fellow in Natural Language Processing available at the Department of Informatics.

The fellowship period is three years.

Depending on the candidate and the teaching needs of the department, the fellowship period can be extended either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up to four years.

Starting date no later than October 1, 2026.

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

Place of work is the Language Technology Group at the Department of Informatics at Blindern, Oslo.

Job description

The Language Technology Group (LTG) at the UiO Department of Informatics (IFI) is an inter-nationally recognized research environment in natural language processing.  The group currently comprises five permanent faculty and around 20 doctoral and post-doctoral researchers.  LTG participates in high-visibility Norwegian and European initiatives, including a national center for research excellence, two national centers for research-driven innovation, and the European flagship initiative OpenEuroLLM, on building a family of fully open and transparent large language models for the languages of Europe, as well as the Horizon Europe project High-Performance Language Technologies (HPLT).  The group represents extensive experience and expertise in web-scale data curation, development of large language models (LLMs), and in-depth LLM evaluation.  LTG has a strong commitment to open-source resource and software development.  Much of the work at LTG, though not all of it, is focused on the languages of Norway, Scandinavia, and Europe. 

 For additional background, please see:

https://www.mn.uio.no/ifi/english/research/groups/ltg/
https://openeurollm.eu
https://hplt-project.org

LTG has a vacancy for a fully funded doctoral fellowship.  The thematic specialization of this position can be adjusted to some degree to the background and research interests of the successful candidate.  The overarching theme will be the interplay of training data composition (e.g. different types and selections of data) and fine-grained evaluation in the development of large language models.  LTG members have access to large-scale computational resources through national and European HPC allocations, and this doctoral fellowship is expected to have a strong experimental component.  Candidate research questions for the fellowship include measurable downstream effects of different mixtures of data in various stages of model training and refinement, combined with the search for methodological advances in evaluation, for example with respect to different model capabilities or adaptability to specific tasks or domains.  It is expected that this work will have its focus on “lesser resourced” languages, for example the two written variants of Norwegian and the larger Scandinavian family, or other languages or related groups of languages in Europe.  The successful candidate will be invited to associate with the OpenEuroLLM consortium, for example through research collaboration with or research visits to partner sites. 

What skills are important in this role?

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 these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

Required qualifications:

• Master’s degree or equivalent in natural language processing or computational linguistics; alternatively, in computer science or machine learning with a specialization in natural language processing
• Documented knowledge of core machine learning methods and techniques, including at least basic experience with deep neural networks
• Documented good programming and data manipulation skills
• Completed M.Sc. level degree corresponding to a minimum of four years in the Norwegian higher educational system
• Fluent oral and written communication skills in English 

Candidates without a master’s degree have until June 30, 2026 to complete the final exam.

Desired qualifications:

• Experience with deep learning frameworks like PyTorch
• Experience in LLM development and/or evaluation

Language requirement:

• Good oral and written communication skills in English
• English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:
  https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8

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

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see:
http://www.mn.uio.no/english/research/phd/

All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation.

What are we looking for in you?

Personal skills:

We are looking for a new member to join a vibrant and diverse research group.  In particular, we value the following personal skills:

• Ability to work both independently and as part of a team
• Ability to work in a structured manner and to adapt to new tasks
• Good communication and collaboration skills
• Positive attitude and the ability to handle hectic periods
• Desire to engage with the research group on-site and contribute professionally and socially

Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications.

We can offer you

• A pleasant and stimulating work environment
• Good welfare schemes
• Opportunity of up to 1.5 hours a week of exercise during working hours
• A workplace with good development and career opportunities
• Career development programmes
• Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
• Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund 

We need different perspectives in our work

UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no.

We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one?

We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures.

If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian).

The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. 

We hope you will apply for the position with us.

How to apply

The application must include:

• Cover letter, including a statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• Transcripts of records, copies of the original Bachelor and Master’s degree diploma (see below)
• An example of academic work, e.g. BS.c. or MS.c. level thesis or a publication
• Documentation of English proficiency if applicable
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system.

When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language.

General information

The best qualified candidates will invited for interviews.

Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.

Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.  

The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.