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years with both research and other career-promoting work. This will be clarified in the recruitment process. A career plan will be prepared that specifies the competencies that the Research Fellow will
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, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from
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. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load
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in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
application process here. About the position The Department of Department of Mechanical and Industrial Engineering is offering an exciting PhD position within the Norwegian Maritime AI Centre , a national
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, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory Familiar with machine learning and deep learning Programming experience (Python or Julia) and their
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, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position The Department of Department
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16th August 2026 Languages English English English The Department of Civil and Environmental Engineering has a vacancy for a PhD in Predictive AI-Based Maintenance and Optimization of Building
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efficient and secure operation of low-carbon power systems. The project will focus on market coupling, optimal pricing in market clearing, flow-based capacity allocation, interconnectors modelling, and market