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distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this post-doc is to develop an inverse super-resolution method based on the use of diffusion model, inspired
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scattering with pair distribution function analysis, in order to complement the optical and NMR spectroscopic results on the photoswitchable systems and derive the structure-property relationship. For
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Université de Technologie de Belfort-Montbéliard | Belfort, Franche Comte | France | about 1 month ago
Additional Information Benefits This PhD is funded by the ANR project DynOpt4Lattice (Agence Nationale de la Recherche). The host institution is the Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB
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13 Sep 2025 Job Information Organisation/Company CNRS Department Chimie du solide et de l'énergie Research Field Chemistry » Physical chemistry Chemistry » Computational chemistry Researcher Profile
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-Markovian effects due to plasticity, and the time intermittency of the fluid flow. The aim is to explain universal distributions of fragments. Knots, Links, and Entanglement – In turbulent flows, fibers can
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25 Sep 2025 Job Information Organisation/Company University of Bordeaux Department Institut de Mécanique et d'Ingénierie de Bordeaux Research Field Engineering » Other Physics » Other Psychological
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2 Oct 2025 Job Information Organisation/Company Laboratoire National de Métrologie et d'Essais - LNE Research Field Mathematics Computer science » Digital systems Physics Researcher Profile
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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of supercomputing libraries for supercomputers. The position is located at Maison de la Simulation team (https://mdls.fr), in Saclay (near Paris), but our team is distributed in the following other locations: Inria
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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