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- NTNU Norwegian University of Science and Technology
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the Research Council of Norway and the partners for the period 2026-2030. There will be approximately 25 doctoral scholarships and some postdoc positions. More information can be found here: https://www.ntnu.edu
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by the Research Council of Norway and the partners for the period 2026-2030. There will be approximately 25 doctoral scholarships and some postdoc positions. More information can be found here: https
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testing Handling mammalian cells and/or organoids Flow cytometry/FACS Molecular biology methods (e.g, DNA work, PCR, etc.) Documented oral and written fluency in English. Nordic applicants can document
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may include methods such as anomaly detection techniques or simulation-based testing. This position offers the opportunity to work at the intersection of cybersecurity, data sharing, and maritime AI in
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complex physical phenomena than those represented in simulations, such as heating system dynamics or occupant behavior. Finally, existing legacy building automation systems may not be well-suited to support
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magnets, unconventional magnetic systems, and topological materials. The candidate will develop and apply advanced computational techniques, including (TD)DFT and post-DFT analyses, alongside spin dynamics
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computational study (atomistic modeling) focusing on the equilibrium and dynamics of gas and water molecules in porous materials Probing different stable structures of gas and water in (and possible reactions
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education until obtaining a doctorate Carry out computational study (atomistic modeling) focusing on the equilibrium and dynamics of gas and water molecules in porous materials Probing different stable
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edge intelligence Knowledge of accelerator simulators Strong knowledge in deep learning, particularly dynamic neural networks Experience with accelerator performance modelling Strong academic writing
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relevant topic in machine learning, embedded systems, and edge intelligence Knowledge of accelerator simulators Strong knowledge in deep learning, particularly dynamic neural networks Experience with