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performance. The research will involve working with large-scale datasets and may include the use of advanced data analysis or AI-based methods to support modelling, uncertainty analysis, and systemic risk
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. The project’s PI is Associate Professor Iselin Åsedotter Strønen. For more information about the project, see https://www4.uib.no/en/research/research-projects/invisible-women-of-the-sea-gendering-fishery
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benchmarking of large language models (LLMs). The research profile of the group is heavily machine-learning oriented and the group has access to excellent HPC infrastructure. For more information about LTG
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project seeks to advance our knowledge on the intended and unintended consequences of punishment, using Norway as a case study. The project will employ population-wide register data and experimental methods
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policy analysis. The project’s PI is Associate Professor Iselin Åsedotter Strønen. For more information about the project, see In/visible women of the sea. Gendering fishery politics and advocacy (GENMAR
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1 Mar 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department The Faculty of Natural Sciences Research Field Biological sciences » Biology Researcher
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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Fundamental knowledge and experimental background in sensors, data acquisition, and electrical actuators Good knowledge of English, both written and oral, is also required. Admission in Engineering and Science
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13 Mar 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Ocean Operations and Civil Engineering Research Field Computer science