137 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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machine-learning methods to enhance predictive capability and enable adaptive process control. Experimental work will include laboratory- and industrial-scale forming trials, supported by comprehensive
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Knowledge about energy systems, especially the operational characteristics of renewable energy production (wind/solar) and batteries Knowledge and interest in applying AI/machine learning to time-series data
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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 Complete your doctoral education leading
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energy applications. You must have experience with data analysis, machine learning, or AI-supported methods applied to engineering or safety problems. PLEASE NOTE: For detailed information about what the
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, you can expect: An attractive and supporting learning environment Participation in research groups Close supervision Skilled supervisors Excellent job prospects The programme is administered by
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Innovation, SFI-CELECT (Research Centre for Effective Engineering and Learning in Complex Systems) . The positions are 3-year doctoral research fellowships starting in 2026. The PhD candidates will be embedded
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. The project will contribute to research within human–computer interaction and human factors on topics including: human–AI teaming in safety-critical work AI transparency and explain-ability in operational
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at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree, with a learning outcome corresponding to the descriptions in the Norwegian
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cooperate in interdisciplinary team You have good communication and dissemination skills You have good analytical and critical thinking skills You have a genuine interest in research and willingness to learn
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of interactive AI agents that can support human learning in complex, safety-critical environments. Human-centered AI in this project means that the agent will learn from simulator data and expert knowledge, and