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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
(Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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26 Aug 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Electronic Systems Research Field Computer science Researcher Profile
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decision-making, computational efficiency, generalization under changing market conditions, and safe constraint handling. The PhD candidate will develop and validate decision-support methods based on deep
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Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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education programme Carry out high quality research Develop material integrity predictive framework using different experimental and simulation approaches Participate in project meetings with supervisors and
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-neutral industries, with a particular focus on the interaction between AI data centers, direct air carbon capture (DAC), district heating networks, and other industrial processes that can effectively
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loading. The project combines computational mechanics, nonlinear finite element analysis and soil–structure interaction to address critical challenges in civil protection and societal resilience. Are you
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completed a PhD in engineering or computer science, or an equivalent foreign doctoral degree recognised as comparable to a Norwegian PhD. Competence in developing and applying machine learning methods Good
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Networked Interactions with Robotics Avatars available at Department of Informatics. The fellowship period is three years. Depending on the candidate and the teaching needs of the department, the fellowship
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and use it to compare wear rates, antagonist interactions and failure mechanisms of conventional and emerging crown materials. Building on the Oslo wear model, the project will adapt wet abrasion