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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
gain admission to the PhD programme in Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of
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Qualifications and personal qualities: You must: Hold a relevant master's degree in any of the following disciplinary fields: social sciences, education, science and technology studies (STS), philosophy or other
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within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment. As an employee at NTNU, it is important that
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New York (USA). Publication: Candidates are encouraged to publish in top-tier venues across machine learning (e.g., NeurIPS, ICML), statistics, and computational biology. Dual Affiliation: The position
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30th September 2026 Languages English English English Build AI digital twins for real-time fermentation control and drive the future of biotech PhD scholarship within Bioprocess Engineering Apply
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relevant Master's degree in mathematical sciences or equivalent, in particular computational mathematics, numerical analysis and experience with AI tools. Your course of study must correspond to a five-year
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engineering disciplines, including structural mechanics, hydrodynamics and machine learning Strong programming skills in Python and/or MATLAB Experience with scientific computing, CFD/FEM software, potential
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particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme Engineering You must have high proficiency in both written and oral English We can not
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You must have a relevant Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or other relevant disciplines. Your course of study must correspond to a five-year Norwegian
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6 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Architecture and Planning Research Field Architecture Researcher Profile