249 Computer-Science-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Norway
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16 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Computer Science Research Field Computer science Researcher Profile
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25 Sep 2026 Job Information Organisation/Company University of Oslo Research Field Medical sciences Researcher Profile First Stage Researcher (R1) Positions Master Positions Application Deadline 16
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16 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Computer Science Research Field Computer science Researcher Profile
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16 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Computer Science Research Field Computer science Researcher Profile
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research agenda and academic environment of the APPROPRIATE project. The PhD candidate must take part in the Faculty of Social Sciences’ approved PhD program (TIK track) and is expected to complete
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project. The PhD candidate must take part in the Faculty of Social Sciences’ approved PhD program (TIK track) and is expected to complete the project within the set fellowship period. For more information
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-ranked international journals. Qualifications and personal qualities: Applicants must hold a master's degree or equivalent education in engineering, informatics, mathematics or physics, or have submitted
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strategic use of this infrastructure in pioneering research on functional materials, photo- and electrocatalysis, and technology development within sustainable energy conversion. Computational materials
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, Computational engineering or applied mathematics, Data science or Artificial intelligence. You must have a Master's degree in above listed areas or equivalent. Your course of study must correspond to a five-year
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agreed with the Head of Department. You must have completed a doctoral degree in information systems, computer science, civil engineering, building information modelling, digital twins, knowledge