Postdoctoral Research Fellow in Machine Learning
- Tromsø, Troms og Finnmark
- Midlertidlig
- Fulltid
- Goal: Develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data.
- Start date: Fall 2026
- Duration: The appointment is for 3 years
- [1] Salomonsen, C. "
" Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024. * [3] Trosten, D. J. "
" Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023. * [4] Wang, J. "
." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.Want to know more?For further information about the position and UiT is available by contacting the principal supervisor and project leader :
- phone: +47 77623216
- email:
- 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
- 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
- Involvement in an interesting research project
- 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
- Application letter
- CV
- Diplomas and transcripts (all degrees)
- Explanation of the grading system for foreign education (Diploma Supplement if available)
- Documentation of
- Contact information to 2-3 references
- Link to the PhD thesis and code repositories from previous projects.
- List of works and description of these:
- You may submit up to 10 works (published or unpublished) that you wish to have considered during the assessment process. Your doctoral thesis will count as one work. Additionally, you must provide a description of your scientific production, highlighting the works you consider most important, which will form the main focus of the assessment. A brief description of the remaining works should also be included to demonstrate the depth of your production. These descriptions must be attached to your application.
- 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