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to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and
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between multiscale flows involving ocean surface waves, submesoscale current, turbulence, and wind actions. The research aims to derive a highly accurate and efficient theoretical models by extending newly
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System Model, vesion 3 (NorESM3), and a central satellite dataset for EEI is from the Clouds and the Earth’s Radiant Energy System (CERES). The specific tasks intended for the PhD fellow are to (i) Analyze
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are fused with land-surface models using data assimilation. The goal is to develop an adaptive experimental design frame-work for the observing system to guide ongoing measurement campaigns and targeted
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satellite imagery are fused with land-surface models using data assimilation. The goal is to develop an adaptive experimental design frame-work for the observing system to guide ongoing measurement campaigns
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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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good understanding on the numerical methods used in ice sheet dynamics, experience in code development and in benchmarking ice sheet models. All candidates and projects will have to undergo a check
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-efficiency requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market
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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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publication record in psycholinguistics, Nordic linguistics, corpus linguistics, sociolinguistics, or related fields Experience with R (data wrangling, visualization, statistical modelling) Experience with