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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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and Gjøvik. The Department of Computer Science is one of seven departments in the Faculty of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning and neural networks Basic
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SINTEF Ocean; FME Martrans https://martrans.no/ and the Norwegian Maritime AI Centre https://www.ntnu.edu/mai The research is foreseen to focus on fluid-dynamic properties of the different sail types
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of Information Security and Communication Technology is one of seven departments in the Faculty of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available
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-principles and data-driven methods may also be explored. Depending on the selected application, topics such as thermal and electrical energy storage, demand-side flexibility, temporal load shifting, and
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promising solution for scalable offshore applications where conventional fixed-bottom systems are impractical. These systems consist of multiple interconnected modules subjected to waves, current, and mooring
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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is one of seven departments in the Faculty of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/304519/phd-candidate-in-underwat
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are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be