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frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
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Description The PhD student will join the T4-SECRET team (https://igdr.univ-rennes.fr/en/t4-secret-group-kevin-mace ), a young and dynamic group specialised in the structural and mechanistic study of Type IV
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This three-year international PhD, funded by a CNRS MITI (Mission pour les Initiatives Transverses et Interdisciplinaires) doctoral contract, is conducted in co-tutelle (double degree) between the University
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from fossil fuels. Yet, many industrial and transport applications still rely on combustion due to their need for high energy densities and thermal processes. Electrofuels (e-fuels), produced from
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solution, e.g., event-based computing, which is particularly suitable for low-latency and low-power systems. In this promising computational paradigm, information is created, processed or transmitted only
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Information Eligibility criteria The candidate must: - Hold a PhD in microbiology or cell biology - Have significant experience in fluorescence microscopy: time-lapse, dynamic imaging, multi-channel, etc
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student at the University of Paris-Saclay attached to the doctoral school of Particles, Hadrons, Energy and Nucleus: Instrumentation, Image, Cosmos and Simulation (PHENIICS). This work will be carried out
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: the Center for Nuclear Sciences and Material Sciences (CSNSM), the Laboratory for Imaging and Modeling in Neurobiology and Cancer Research (IMNC), the Orsay Institute of Nuclear Physics (IPNO), the Linear
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a