12 machine "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" uni jobs in Norway
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socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning techniques, we aim to: Improve understanding of risk factors for
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. Department of Computer SciencCountryNorwayCityGjøvikPostal Code2815StreetTeknologivegen 22Geofield Contact City Gjøvik Website http://www.ntnu.no Street Teknologivegen 22 Postal Code 2815 STATUS: EXPIRED X
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, advanced imaging, AI/machine-learning approaches, mathematical modelling, or novel computational methods are especially welcome. The successful candidate will receive a competitive start-up package and join
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-disciplinary. The candidate is expected to work in the Human-Computer Interaction Group (HCI) and collaborate with the Intelligent Information Systems (I2S) Group, the Research Group for Emerging Media, and the
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, machine learning, and robotics. Our goal is to strengthen Norwegian research, education, and innovation in AI, machine learning, and robotics, as well as other relevant fields within artificial intelligence
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are central. We are seeking an associate professor with strong research and innovation competence in human-computer interaction, human-centred design and the design of safety-critical systems and products. We
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and Electric Machines research group (PEM), which is one of four research groups in the department. The main responsibility of the Professor/Associate Professor will be research and teaching within
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insights. Ability to apply system-level thinking, linking infrastructure performance, environmental conditions, and operations. Experience with data-driven modelling or machine learning. Ability to work both
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, specialising in either machine learning or quantum information science. The Department of Information Theory at Simula UiB conducts research on two main areas: statistical learning theory and quantum information
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with researchers in epidemiology, biostatistics, informatics, machine learning, artificial intelligence and precision medicine. The Department leads the UiO:Real-World Evidence (UiO:RWE) convergence