진학프로석·박사 채용 접수 플랫폼

The position

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 positions aim is to develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data.

General information about the position.

The position is a fixed term position for a duration of 3years. Appointment to the position of Postdoctoral Research Fellow 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 position as a Postdoctoral Research Fellow at the same institution.

The workplace is at UiT in Tromsø. You must be able to start in the position 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, that is 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 already 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 is available by contacting the principal supervisor and project leader Associate Professor Kristoffer Wickstrøm:

• phone: +47 77623216
• email: kristoffer.k.wickstrom@uit.no

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

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, as well as the northernmost university in the world and well connected to the rest of Europe. Located on an island surrounded by fjords and mountains, Tromsø is a major cultural hub within the Arctic Circle and a great spot for outdoor activities (hiking, skiing, etc.).

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 then the Faculty of Science and Technology may reimburse your moving costs. Further details regarding this matter will be made available if you receive an offer from us.

Norwegian health policy aims to ensure that everyone, irrespective of their personal finances and where they live, has access to good health and care services of equal standard. As an employee you will become member of the National Insurance Scheme which also include 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 i Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity is a strength, and we want employees with different competencies, professional experience, life experience and perspectives.

If you have a disability, a gap in your CV or immigrant background, we encourage you to tick the box for this in your application. If there are qualified applicants, we invite least one in each group for an interview. If you get the job, we will adapt the working conditions if you need it. Apart from selecting the right candidates, we will only use the information for anonymous statistics.

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 to 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 description of these. The list of works shall contain the following information:
  • author(s), the work’s title
  • the journal’s/conference’s/book’s name and year of publication
• 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 for the position, provided that you submit parts of your dissertation along with your application. This enables the evaluation committee to assess the quality and likelihood of completion by the desired employment date. You must include a statement from your supervisor or institution stating the expected completion date for your PhD degree. Documentation of your completed PhD degree must be submitted before commencement.

All documentation to be considered must be in a Scandinavian language or English. (If English proficiency is not documented in the application, it must be documented before starting in the position). We only accept applications and documentation sent via Jobbnorge within the application deadline.

Assessment

The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications based on the written material presented by the applicants, and the detailed description draw up for the position. A copy of the assessment report will be sent to all applicants.

The applicants who are assessed as best qualified will be called to an interview. The interview should among other things, aim to clarify the applicant’s motivation and personal suitability for the position. A trial lecture may also be held.

General information

The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants.

The engagement is to be made in accordance with the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment. After the appointment you must assume that there may be changes in the area of work.

The remuneration for Postdoctoral research fellow is in accordance with the State salary scale code 1352. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the Norwegian Public Service Pension Fund, which gives you many benefits in addition to a lifelong pension: You may be entitled to financial support if you become ill or disabled, your family may be entitled to financial support when you die, you become insured against occupational injury or occupational disease, and you can get good terms on a mortgage. Read more about your employee benefits at: spk.no.

The successful candidate must be willing to get involved in the ongoing development of their department and the university as a whole.

UiT wishes to promote gender equality. If two or more applicants are found to be equally qualified, the university will rank applicants from the underrepresented gender ahead of others.

According to the Norwegian Freedom and 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.

Eallju - Developing the High North

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 this motive power at UiT. Along with students, staff and the wider community, we aim to utilise our location in Northern Norway and Sápmi, our broad and diverse research and study portfolio and interdisciplinary advantage to shape the future.

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 in the entire range from basic to applied. We will convey knowledge about disciplines and contribute to innovation. Our social mission unites UiT across various studies, research fields and large geographical distances. This demands good cooperation with trade and industry and civil society as well as with international partners. We will strengthen knowledge-based and sustainable development at a regional, national and international level.

Academic freedom and scientific and ethical principles form the basis for all UiT’s activities. Participation, co-determination, transparency and good processes will provide the decision-making basis we need to make wise and far-sighted priorities. Our students and staff will have the opportunity to develop their abilities and potential. Founded on academic integrity, we will be courageous, committed and generous in close contact with disciplines, people and contemporary developments.

We will demonstrate adaptability and seek good and purposeful utilisation of resources, so we are ready to meet the expectations and opportunities of the future. We will strengthen the quality and impact of our disciplines and core tasks through the following three strategic priority areas.