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implementation and data handling; iv) contribute to the intercomparison with simulations and outputs of one model (CISM); v) collect, organize and quality check output data from the participating modelling groups
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29th September 2025 Languages English English English PhD Research Fellow in ICT – Benchmarking, Evaluating, and Improving Trustworthy Language Models Apply for this job See advertisement About the
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Technology is excitedto announce a vacant position of Postdoctoral Research Fellow in the area of sea ice model parameter optimization with Earth Observation data at UiT The Arctic University of Norway
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the methodologies for preventing unintended, harmful behaviors in open-source AI models. Your work will focus on the foundational challenges of safety, from mitigating algorithmic bias to ensuring systems remain
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of NORCE Norwegian Research Centre there is a 3-year full time PhD research fellow position available within the field of modeling and simulation of CO2 storage. The position is for a fixed-term period of 3
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models to resolve blade loads and structural responses under both operational and extreme conditions, including scenarios with partial out-of-water exposure Uncertainty quantification to ensure robust and
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of realistic inflow environments and their impact on turbine performance Assessment of clearance effects on loads and efficiency near the sea surface and seabed Development and use of multi-fidelity models
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, specifically large language models (LLMs), and general-purpose AI become more ubiquitous, they introduce novel and complex attack surfaces. Your mission will be to proactively investigate these vulnerabilities
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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