430 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Linköping university" Fellowship positions in Norway
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stimulating research environment. The project will be supervised by Prof. Rafal Ciosk and co-supervised by Prof. Marianne Fyhn: https://www.mn.uio.no/ibv/personer/vit/rafalc/ https://www.mn.uio.no/ibv/english
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position see https://www.visual-intelligence.no/about/open-positions . We expect that you will engage in collaborative research with other members of the centre and the research group. You will collaborate
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Simula UiB (https://simula-uib.com ) is a
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
inform the development of innovative, mechanics-based intervention strategies. By focusing on the biomechanics of cancer cell spreading, GLIOFORCE seeks to open new avenues for the treatment of aggressive
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, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be an attractive and inclusive place to study and
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career within or beyond academia. To support a strategic and well-structured PhD trajectory, the PhD fellow will be required to develop a career and competence development plan in dialogue with
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contribute to sustainable and democratic development and be an attractive and inclusive place to study and work. PhD position There is a vacancy for a PhD Research Fellow in Snow Processes in Mountainous
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be among Europe's leading universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development
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which also include health care services. More practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will
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data with good utility. This project involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation