33 computational-physics "https:" "https:" "https:" "https:" "Caltech" uni jobs at Nature Careers in France
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of this project, you will have developed deep networks in both the quantum and healthcare industries to ideally position yourself for the transition to your next role. The Quantum Program Manager position offers
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, as reliable decisions must often be produced from partially observed data. Event-based sensing and neuromorphic computing offer promising paradigms to address this challenge by providing asynchronous
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city at the heart of Europe. The position will be supported by an attractive start-up package. The application deadline is March 15, 2026 and the interviewing process is expected to commence in early May
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of Research for Condensed Matter and Physical and Material Sciences, who together lead the Experiments Division. See https://www.esrf.fr/about/organisation/organisation-chart for an overview
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researchers in the implementation of their research programme at the host institution. (https://www.fnr.lu/funding-instruments/pearl/) Your Profile… Outstanding track record in the field of translational
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neuroscience, clinical neurology, population neuroscience, mathematics and computer science. It has 12 cutting-edge core facilities for data generation across various scales and modalities (genomics
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of Geography and Spatial Planning (https://dgeo.uni.lu ), joining the Economic Geography team of Prof. Christian Schulz. The position contributes to the INTERREG-NWE funded AccessHubs project, which examines
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Department of Geography and Spatial Planning (https://dgeo.uni.lu ) and participate to its activities Your profile Master's degree in human geography, spatial economics, or a quantitative social science field
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
in Computer Vision; 2009 Oct 12–16; Trégastel, France.Available from: https://inria.hal.science/inria-00404638v1/document 5. Micicoi G, Grasso F, Kley K, Favreau H, Khakha R, Ehlinger M, et al
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, https://hal.science/hal-04930868 . [2] Peyré, G., Cuturi, M., et al. (2019). Computational optimal transport: With applications to data science. Foundations and Trends in Machine Learning, 11(5-6):355–607