4 PhD Fellows in Deep Learning at Visual Intelligence Research Centre and UiT Machine Learning Group

Monday 2nd June 2025

Contact Email for the Job Posting elisabeth.wetzer@uit.no
Organization UiT The Arctic University of Norway
Location Tromsø, Norway
Title 4 PhD Fellows in Deep Learning at Visual Intelligence Research Centre and UiT Machine Learning Group
URL https://www.jobbnorge.no/en/available-jobs/job/280768/4-phd-fellows-in-deep-learning-at-visual-intelligence-research-centre-and-uit-machine-learning-group
Closing date Jun 17, 2025
Description As a Visual Intelligence researcher, you will contribute to solving the pressing societal challenges of our time for a sustainable future. You will contribute important new solutions within healthcare and precision medicine, be at the forefront in marine ecosystem monitoring by AI, enable novel methods for more efficient use of energy resources or infrastructure, and help develop better ways to observe the Earth from space to benefit the planet and to aid decision-making. This will be done by collaborating with VI consortium partners from industry and the public sector to create new innovations to benefit Norwegian value creation.
3 of the PhD positions are funded through the center's budget, and one position is funded by a UiT's interdisciplinary project called the Consortium for Patient-Centered AI (CPCAI).
For all 4 positions, potential directions are to research new ways to
- Represent the general properties of relevant and real-world data by self-supervised learning towards AI foundation models.
- Represent general properties of data coming from different sources, i.e. multimodal AI models (combining images, text, etc).
- Understand the important mechanisms of the AI models in terms of their prototypical behaviour, individual neurons or layers within networks, or the quality of the data (data-centric intelligence).
- Develop interpretable generative AI solutions.
- Develop new methodology to improve the robustness and reliability of deep learning models.
Each of the 4 positions has a different innovation area:
Position 1: This position will have a medical and health innovation focus and will collaborate with one or more of the consortium’s health partners: the University Hospital of North Norway, The Cancer Registry of Norway, GE Healthcare. The candidate will develop new solutions in one or more areas such as (multimodal) MR and/or CT-based tumor segmentation and quantification, mammography-based breast cancer, or cardiac ultrasound for early detection of heart diseases.
Position 2: This position will have an energy innovation focus and will collaborate with one or more of the consortium’s energy partners: Equinor and Aker BP. The candidate will potentially work on energy foundation models based on seismic data for more efficient use of energy resources, may develop methods for characterizing the subsurface within palynology (e.g. digitized microfossil analysis), or be engaged in energy infrastructure monitoring.
Position 3: The innovation area for this position will be determined upon examination of the applicants with respect to methodological research potential or based on the consortium’s needs. Relevant innovation areas are within marine ecosystem monitoring, within medicine and health, within energy, earth observation, or a combination of use cases from all these application areas.
Position 4 (CPCAI): The innovation area of this position is within deep learning for decision and diagnosis support by analysis of data from electronic health records (EHRs). This position is conducted in collaboration with the University Hospital of North Norway and the CPCAI project. EHRs are by nature multimodal and the safe exploitation of EHRs are key for the future of the healthcare system. Potential directions include best possible multimodal representation learning in EHRs, predictions of adverse outcomes after surgery, and causal discovery (treatment-effect-counterfactuals).