38 molecular-modeling-or-molecular-dynamic-simulation Fellowship positions at UiT The Arctic University of Norway in Norway
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Chemistry » Molecular chemistry Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country Norway Application Deadline 29 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job
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Stig Brøndbo 29th October 2025 Languages English English English Faculty of Health Sciences Postdoctoral Research Fellow within microbiology and molecular biology Apply for this job See
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Lars Åke Andersen 28th September 2025 Languages English English English Faculty of Health Sciences PhD Fellow in Molecular Cell Biology/Autophagy Apply for this job See advertisement The position
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. The research topic of this PhD is Accurate and Scalable Simulation of Edge Systems.You will be part of the Cyber-Physical Systems group . General information about the position. The position is for a period of
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Stig Brøndbo 26th October 2025 Languages English English English Faculty of Science and Technology PhD Fellow in Computer Science - Accurate and Scalable Simulation of Edge Systems Apply
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-incorporated ridging scheme in the state-of-the-art neXtSIM: next-generation sea-ice model. The postdoc will work directly with other members of the DynAMIC team, including project investigators and the PhD
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-generation sea-ice model. The postdoc will work directly with other members of the DynAMIC team, including project investigators and the PhD Student. The candidate will further join a growing team of
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Stig Brøndbo 4th August 2025 Languages English Norsk Bokmål English English Faculty of Engineering Science and Technology PhD Fellow in signal processing and modelling in the seafood industry Apply
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advertisement The position A PhD position is available at the Department of Clinical Medicine, Faculty of Health Sciences, UiT. The position is affiliated with the Molecular Inflammation Research Group (MIRG) and
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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