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a highly motivated candidate for a full-time (100%) PhD position for 3 years in “Development of Probabilistic Reliability Criteria in Distribution Grids”. You will join the research group Power System
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a PhD candidate, you will benefit from close supervision, access to an international research community, strong industry connections, and excellent opportunities for academic development. Are you
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27th April 2026 Languages English English English The Department of Electric Energy has a vacancy for a PhD Candidate in “Development of Probabilistic Reliability Criteria in Distribution Grids
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and research partners from a variety of fields, spanning from marine technology, cybernetics to biology, biotechnology and product development. NTNU is responsible for supervising the PhD and
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. Duties of the position Complete the doctoral training and successfully obtain a PhD degree Conduct high-quality research within the scope outlined for the position Publish scientific results in recognized
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fields, spanning from marine technology, cybernetics to biology, biotechnology and product development. NTNU is responsible for supervising the PhD and postdoctoral fellowships included in the centre
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degree programmes. We conduct wide-ranging research in fields such as technology, energy, product quality and development, and productivity. The Department of Mechanical and Industrial Engineering is one
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
6th April 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a SFI FAST: PhD position in Microstructure/texture evolution during extrusion
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract