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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the
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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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of national and international funding agencies, as well as from industry. Job description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series
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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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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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treated. HARPNET’s scientific programme is integrated across three scientific work packages, where data, technologies and biological models will be shared across projects through joint supervision, network
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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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-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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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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conduct cutting-edge research on AI-based forecasting and analytics for shipbroking and maritime decision support. The aim is to develop and analyze advanced models that integrate heterogeneous maritime