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16th March 2026 Languages English English English The Department of Structural Engineering has two vacancies for SFI FAST: PhD positions in Modelling Strength and Failure in Recycled Aluminium
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, physics-based models, and data-driven methods to support design, manufacturing, and decision-making across aluminium value chains. Education and competence building are central pillars of FAST. The centre
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and their efficient use. Disseminate results in academic publications and popular science dissemination. Participate in the research group of Knowledge-based engineering and knowledge-driven systems
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15th March 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate in AI-driven condition-based opportunistic maintenance
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structural design, and lifecycle performance. A key outcome of FAST is the development of the FAST Virtual Lab, a digital framework combining experimental data, physics-based models, and data-driven methods
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of Marine Technology , as part of the Norwegian Maritime AI Center (MAI) at NTNU . As a PhD candidate, you will conduct research to develop AI-driven methods for efficient methods for simulation-based testing
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Knowledge of or experience with semantic modeling, knowledge representation and automated reasoning Knowledge of or experience with knowledge-based engineering and system engineering Knowledge
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23 Feb 2026 Job Information Organisation/Company Norwegian University of Life Sciences (NMBU) Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
development of the FAST Virtual Lab, a digital framework combining experimental data, physics-based models, and data-driven methods to support design, manufacturing, and decision-making across aluminium value
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engineers, and comparisons with current document‑driven approaches. We are aiming at improvements in the visibility of dependencies, the assessment of change impacts, and the potential for AI‑assisted