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metocean and biogeochemistry models accounting for climate change impacts across Europe (from the Nordic Seas to the Black Sea and Mediterranean Sea) and the Pan-Arctic region. The PhD project focuses on new
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event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components. About the LEAD AI fellowship programme LEAD AI is the University
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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tools (e.g., drones, 3D mapping) for high-resolution geological mapping and rock mass quality assessment. Develop and calibrate numerical models using field data and case studies to simulate various
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amine-based CO2 capture plants. This position at the Department of Chemical Engineering at NTNU focuses on chemical absorption and, more specifically, on the modelling of solvent degradation. Carbon
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with machine learning and pattern recognition tool development All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be
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combination with multi-fidelity response models. The multi-fidelity models may include combinations of physics-based response models, Artificial Intelligence (AI) models and probabilistic methods. Your
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of language models. The research profile of the group is heavily machine-learning oriented and the group has access to excellent HPC infrastructure. For more information about the Language Technology Group (LTG
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31st July 2025 Languages English English English The Department of Civil and Environmental Engineering has a vacancy for a PhD Candidate in Hydrological and Water Resource Modelling in the Himalayan
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) , Department of Biostatistics, Institute of Basic Medical Sciences (IMB), University of Oslo (UiO), Norway. The candidate shall take part in the research group on “Statistical models for high-dimensional and