Postdoctoral Research Fellow in Machine Learning

Arbeidsplassen; Tromsø; On-site; NOK 600,000 - 800,000; Full time

Job summary

A leading Norwegian university in Tromsø is seeking a Postdoctoral Research Fellow in Machine Learning to develop innovative deep learning algorithms for spatio-temporal medical image analysis. The successful candidate will have a Norwegian doctoral degree or equivalent, a strong background in mathematics, and expertise in deep learning methodologies. Flexible working hours and excellent career opportunities are provided.

Benefits

Flexible working hours

State collective pay agreement

Pension scheme available

Reimbursement for moving costs

Qualifications

• Candidate must hold a Norwegian doctoral degree or equivalent.
• Good command of English and excellent communication skills required.
• Strong documented background in mathematics necessary.

Responsibilities

• Develop deep learning algorithms for spatio-temporal medical image analysis.
• Collaborate with the UiT Machine Learning Group.
• Contribute to the ongoing research in machine learning methodologies.

Skills

Expertise in deep learning

Good command of English

Strong background in mathematics

Education

Norwegian doctoral degree or equivalent

Job description

Postdoctoral Research Fellow in Machine Learning

An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology. The position aims to develop new deep learning algorithms for spatio-temporal medical image analysis with a focus on learning from limited labelled data.

The position

The position is a fixed-term appointment for 3 years. Appointment to the Postdoctoral Research Fellow position is mainly intended to provide qualification for work in top academic positions. It is a prerequisite that the applicant can carry out the project over the full course of the employment period. No person may hold more than one fixed-term Postdoctoral Research Fellow position at the same institution. The workplace is UiT in Tromsø. You must be able to start within 6 months after receiving the offer. Starting will be Spring/Fall 2026.

The position's field of research

The position is offered in the context of a UiT grant that focuses on modeling spatio-temporal medical image analysis with a particular focus on learning from limited labelled data. The successful candidate will be a part of the UiT Machine Learning Group and will also be affiliated with the Center for Research-based Innovation Visual Intelligence.

In this context, we are seeking a candidate to take an active role in the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, i.e., medical images that evolve over time, with emphasis on dynamic PET imagery and ultrasound. A special focus will be given to learning from limited labeled data (e.g., few-shot and self-supervised learning and clustering). The position will be part of the ongoing effort to design new deep learning methodology for spatio-temporal medical image analysis [1, 2] and fundamental research within learning from limited labels [3,4].

• [1] Kuttner et al.,Deep learning-derived input function in dynamic [18F]FDG PET imaging of mice, Frontiers in Nuclear Medicine, 2024
• [2] Sarina et al., Light-weight spatio-temporal graphs for segmentation and ejection fraction prediction in cardiac ultrasound, MICCAI, 2023
• [3] Trosten et al., Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings, CVPR, 2023
• [4] Wang et al., AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering, CVPR, 2025.

Contact

For further information about the position and UiT, please contact the principal supervisor and project leader Associate Professor Kristoffer Wickstrøm:

• phone: [phone]
• email: [e-mail]

Qualifications

This position requires:

• a Norwegian doctoral degree in the subject area concerned or a corresponding foreign doctoral degree recognized as equivalent to a Norwegian doctoral degree.
• good command of English and excellent communication skills
• a strong documented background in mathematics

Special emphasis will be given to candidates with prior experience in the above-mentioned topics as well as the quality of prior publications. Experience in biomedical interdisciplinary work is a plus.

We are looking for a candidate who:

• is independent thinking and enjoys working in a team
• has expertise in deep learning
• is motivated for scientific work, and has excellent analytical and collaborative features

The main purpose of postdoctoral research fellowships is to qualify researchers for work in top academic positions within their discipline and this requires a strong commitment from the candidate.

In the assessment the main emphasis will be attached to the submitted works and the project proposal for the qualifying work. Emphasis shall also be attached to experience from popularization/dissemination and academic policy and administrative activity.

At UiT we put emphasis on the quality, relevance and significance of the research work and not on where the work is published, in accordance with the principles of The San Francisco Declaration on Research Assessment (DORA).

Location

The UiT Machine Learning Group is located in Tromsø, a lively town with approximately 75,000 inhabitants. It is known for its beautiful scenery, northern lights, midnight sun, and the northernmost university in the world. Tromsø is on an island surrounded by fjords and mountains, a major cultural hub within the Arctic Circle.

We offer

• Involvement in an interesting research project
• Good career opportunities
• A good academic environment with dedicated colleagues
• Flexible working hours and a state collective pay agreement
• Pension scheme through the state pension fund
• If you have to relocate to Tromsø, the Faculty of Science and Technology may reimburse your moving costs. Further details will be provided if you receive an offer.

Norwegian health policy aims to ensure that everyone has access to good health and care services of equal standard. As an employee you will become a member of the National Insurance Scheme which also includes health care services.

More practical information for working and living in Norway can be found here: https://uit.no/staffmobility

Inclusion and diversity

UiT The Arctic University of Norway is actively promoting equality, gender balance and diversity among employees and students, and aims to create an inclusive and safe working environment. We encourage applicants from diverse backgrounds to apply.

If you have a disability, a gap in your CV or an immigrant background, please indicate this in your application. If qualified applicants exist, at least one from each group may be invited for an interview.

Application

Your application must include:

• Application letter
• CV
• Diplomas and transcripts (all degrees)
• Explanation of the grading system for foreign education (Diploma Supplement if available)
• Documentation of English proficiency
• Contact information for 2-3 references
• A list of your academic production
• Description of your academic production, stating which works you consider most important
• Academic works, up to ten (published or not), you wish us to take into consideration in the assessment. The doctoral thesis is regarded as one work.
• List of works and a description of these. The list of works shall contain: author(s), title, journal/conference/book, year
• Link to the PhD thesis and code repositories from previous projects.

If you're in the final stages of your PhD, you may still apply provided you submit parts of your dissertation. You must include a statement from your supervisor or institution about the expected completion date. Documentation of the completed PhD degree must be submitted before commencement.

All documentation to be considered must be in a Scandinavian language or English. Applications and documentation must be submitted via Jobbnorge within the application deadline.

Assessment

The applicants will be assessed by an expert committee. The committee will assess qualifications based on the written material and the project description. A copy of the assessment report will be sent to all applicants.

The best-qualified applicants will be called for an interview. The interview may include a trial lecture.

General information

The appointment is made in accordance with State regulations and UiT guidelines. The engagement is subject to export control regulations. Candidates who are deemed to conflict with these criteria will be prohibited from recruitment. Changes in the area of work may occur.

The remuneration for Postdoctoral Research Fellow is in accordance with the State salary scale code 1352. A compulsory 2% contribution to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the pension fund with benefits including health, accidental, and disability coverage. Read more at spk.no.

The successful candidate must be willing to contribute to the ongoing development of the department and university.

UiT supports gender equality. If two or more applicants are equally qualified, the university may rank applicants from the underrepresented gender ahead of others.

According to the Norwegian Freedom of Information Act information about the applicant may be included in the public applicant list, even if the applicant has requested non-disclosure.

Om bedriften

UiT The Arctic University of Norway is a multi-campus comprehensive university at the international forefront. Our vision is to be a driving force for developing the High North. The Northern Sami notion eallju, which means eagerness to work, sets the tone for UiT. Our social mission is to provide research-based education of high quality, perform artistic development and carry out research of the highest international quality standards. We will strengthen knowledge-based and sustainable development at regional, national and international levels.

Academic freedom and scientific and ethical principles guide all UiT activities. We strive for inclusion, transparency and good processes to support wise and far-sighted priorities. We seek to enable staff and students to develop their abilities and potential.

We aim to be adaptable and to use resources effectively to meet future opportunities. We will strengthen the quality and impact of our disciplines through strategic priority areas.