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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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Innovation. The project focuses on detecting radioactive contaminants in liquids. The postdoctoral researcher will participate in the production of materials and contribute to the development of dedicated
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will design
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Institut Polytechnique de Paris, is one of France's top 5 general engineering schools. The mainspring of Télécom Paris is to train, imagine and undertake to design digital models, technologies and solutions
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recreation, ticket sales, etc.) Health Insurance: Mandatory enrollment (unless exempt) in the MGEN plan, with 50% coverage Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8004-PAUBAR-010
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Post-doctoral position (M/F) for testing drought-based BEF relationships at CEFE Montpellier, France
simulation plan and conduct simulations with the Phoreau model, to reach the identified objectives. They will also have to establish transfer functions between model outputs and forest contributions, and carry
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to innovation for patient care. Jean-Léon Maître, head of the “Mammalian Developmental Mechanics” team (https://institut-curie.org/team/maitre ), is seeking a postdoctoral researcher with a strong interest in
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technologies within our laboratory. - Design and develop processes for synthesizing hollow fiber membranes to meet the specific needs of our research and development projects. - Design and develop processes
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Shell Model with Continuum and its extensions to construct high-fidelity microscopic optical potentials, designed for use in few-body reaction formalisms, in particular Faddeev-type calculations targeting
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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform