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preparedness. The position is for a period of three years. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for
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(average grade B or better) or demonstrated research potential (NTNU's grading scale ) Must meet admission requirements for the PhD programme in Biotechnology at NTNU (faculty's Doctoral Programme (https
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partners (schools, public and private sectors) and engage with the analysis of the collected data. This main goal of this particular PhD fellowship is to explore how humans interact with the automatically
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12th January 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Human-AI Interaction and Learning Apply for this job See advertisement
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technology Computer science » Cybernetics Physics Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 18 Jan 2026 - 23:59 (Europe/Oslo) Type
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, rehabilitation, and care. Common for all research areas within health sciences are human health on micro and macro levels, where the interaction between individual, interhuman and societal conditions are central
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application for admission to a PhD programme at the institution. The documentation that is necessary to ensure that the admission requirements are met must be uploaded as an attachment. Main tasks The PhD
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description About the position The Department of Marine Technology at NTNU has a PhD position related to optimal
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to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position. The engagement is to be made in accordance
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detailed data about forest ecosystems. To convert the captured data into meaningful information about the forest environment we seek a PhD candidate who wishes to advance state-of-the-art computer vision