20 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" Postdoctoral positions in Norway
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program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt over besøkene dine på
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at SLATE. The position is for a fixed term of four years, with the inclusion of career development work (e.g., teaching, project work) accounting for 25% of the entire period, and is financed by University
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of career development work (e.g., teaching, project work) accounting for 25% of the entire period, and is financed by University of Bergen. The position is open to an incoming candidate, se LEAD AI mobility
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be associated with the new national AI LEARN Centre at SLATE. The position is for a fixed term of four years, with the inclusion of career development work (e.g., teaching, project work) accounting
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with radioactive sources and at beamlines to test the performance of the NOVO prototype. Contribute to the development and testing of AI-algorithms for image reconstruction. Support NOVO staff working
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and industry partners. Together, we aim to strengthen the sustainability of Norwegian agriculture to face internal and global challenges. As a postdoc, your role will be central to developing AI-driven
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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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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25. september 2025 Språk Norsk Bokmål Norsk Bokmål Norsk Bokmål Postdoctoral Position on Safety Training and Preparedness in the Arctic - Arctic Safety Centre Søk stillingen Se annonse About us UNIS
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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