14 computer-science-phd PhD positions at NTNU Norwegian University of Science and Technology
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can be extended by 10 weeks after completed and documented the Norwegian course. For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Biology within
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to the PhD programme in Materials Science and Engineering (https://www.ntnu.edu/studies/phmt ) within three months of your employment contract start date, and that you participate in an organized doctoral
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Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 15 Nov 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per
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requirements for admission to the faculty's doctoral program (PhD Programme in Medicine and Health Sciences - NTNU ). PLEASE NOTE: For detailed information about what the application must contain, see paragraph
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Technology » Energy technology Environmental science Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 31 Oct 2025
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to the PhD programme in Computer Science within three months of your employment contract start date, and that you participate in an organized doctoral programme throughout the period of employment
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doctorate and open up exciting career opportunities related to the energy transition in Norway? The Department of Computer Science (IDI) at NTNU has a vacancy for one PhD fellowship in the intersection
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PhDCandidate, it is a prerequisite that you gain admission to the PhD programme in Electric power Engineering within three months of your employment contract start date, and that you participatein an organized
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document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's doctoral program in Engineering Good written and oral English language skills
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Cybernetics at NTNU is offering a fully funded PhD position in the area of learning-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks