61 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Nature Careers in France
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role The University of Luxembourg (UL) invites applications for a postdoctoral researcher position within the Department of Computer Science (http://dcs.uni.lu ). The candidate should have a research
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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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(https://research.pasteur.fr/en ). Located in central Paris, it offers an unparalleled research environment with state-of-the-art laboratories and core facilities (technological platforms, animal
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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
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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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INT-26028 INTERNSHIP IN ORGANOMETALLIC CHEMISTRY FOCUSED ON DESIGNING NOVEL CATALYSTS FOR ADDITIV...
, motivated, and excited to work at the frontier of sustainable materials science, this internship will give you a unique chance to grow, learn, and contribute to the future of ecofriendly tire technology. Is
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The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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for experimentation, yet they remain difficult to deploy directly onboard robots due to hardware availability, latency, sampling cost, and noise. Previous work on quantum machine learning (QML) emphasize