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workshops, seminars, and other dissemination activities ; - Assist other members of the hosting team, including more junior researchers (phds) in their research. The selected candidate will be based
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disciplines and involve expertise in optics, electronics, image and data processing using machine learning, photophysics, chemistry and biology. The position is therefore particularly well suited for candidates
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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in one of the following areas (or related fields): * Machine learning / deep learning * Quantum computing / quantum
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for the rapid and effective treatment of severe traumatic wounds, particularly in civil or military emergency situations. This new system aims to combine strong adhesion in wet environments, on-demand UV
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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microtubules (Anna Akhmanova, University of Utrecht, Netherlands). The "Physics of Cells and Cancer" unit (UMR 168) brings together physicists and biologists working to discover the role of physical laws in
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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria We are looking for a colleague with a PhD in particle physics. Experience with machine learning and/or experience with
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- pan-Arctic simulations with ISBA - learning how to use permaFOAM - gathering of data necessary to use permaFOAM on the Abisko site - analysis and comparison of the ISBA and permaFOAM simulations