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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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nucleation pathways related to different emissions characteristics at the engine exhaust. The collected data would be helpful to validate the microphysics models for ice nucleation process, hence clarifying
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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Science in Earth Observation develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth
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data would be helpful to validate the microphysics models for ice nucleation process, hence clarifying the different nucleation pathways for ice formation. You will collaborate with other researchers
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power electronic conversion, energy and hydrogen storage, downstream processes
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and uncover yet unknown physiological particularities of sleep and other human health factors. Your Profile PhD (or near completion) in Biomedical Engineering, Computer Engineering, Computer
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physics and biology. The institute also benefits from state-of-the-art core facilities, particularly in microscopy (Microscopy Rennes Imaging Center, MRic, https://microscopie.univ-rennes1.fr/ ). Rennes is
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expertise in in vivo two-photon imaging to study how cortical circuits represent and regulate immune responses. Our group focuses on the “neuroscience of immune responses,” applying circuit-level and systems