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engineers and researchers are scarce globally. Candidates who complete a PhD within the SAINT project will be well positioned for careers in nuclear safety, maritime regulation, advanced vessel design, and
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of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/307712/phd-candidate-in-explaina… Requirements Research FieldComputer scienceEducation LevelMaster
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
of Engineering. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/307594/phd-candidate-to-conduct-… Requirements Research FieldEngineeringEducation LevelMaster Degree or equivalent Additional
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to apply Website https://www.jobbnorge.no/en/available-jobs/job/299879/phd-candidate-in-structur… Requirements Research FieldMathematicsEducation LevelMaster Degree or equivalent Additional Information Work
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Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/307886/phd-candidate-in-efficien… Requirements Research FieldComputer scienceEducation LevelMaster Degree
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to the IE faculty's Doctoral Programme (https://www.ntnu.edu/ie/research/phd/), see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in Computer Science and
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base. The Department of Energy and Process Engineering is one of eight departments in the Faculty of Engineering. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/307684/phd
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supervisor), Professor Ingunn Studsrød (co-supervisor), and Associate Professor Marina Snipsøyr Sletten (co-supervisor). Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/302556/phd
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“SFI Seaweed - Centre of gravity for industrial seaweed research and innovation” funded by the Research Council of Norway. The PhD position is linked to the “SFI Seaweed - Centre of gravity
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design spaces, long-duration simulations, and real-time applications. This PhD project will develop physics-informed deep learning and surrogate modelling approaches to accelerate simulation, uncertainty