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12th January 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Mutli-Agent Communication to Enhance Human Learning Apply for this job See
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to the computational modelling efforts at the Materials Theory Group. We are seeking a candidate with a strong background in artificial intelligence and machine learning, applied to condensed/soft matter physics
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, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing
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in the research group of Research Prof. Alireza Qaiumzadeh at the Department of Physics, NTNU, Trondheim, Norway. Your immediate leader will be the Head of Department. About the project The PhD project
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position A three-year PhD position in computational condensed matter physics is
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analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work
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at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented knowledge and experience with machine learning or other relevant
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students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position A PhD position, fully funded for three years
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented knowledge and experience with machine learning or other relevant AI Documented knowledge in
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, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Fundamental contributions in embodied AI