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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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these developments to characterize the mechanical behavior of representative systems and support model identification and validation, in close interaction with numerical modeling and data-driven approaches. This will
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UMR 6524, Clermont-Auvergne University. Collaboration with the IMFT (Institute of Fluid Mechanics, Toulouse) for the numerical modelling. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6524
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process modelling. The ideal candidate will possess a strong numerical background with proficient programming skills and a proven research record through publications and code development. Experience in
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this, the CHAIN-H2 project will combine experimental and numerical studies covering small-scale kinetics through to modelling of the larger-scale characteristics of flame inhibition (flame propagation in a cloud of
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), colloidal physics and numerical modelling (LGC, Toulouse), and dense protein systems and drying (STLO, Rennes). The present postdoctoral position, under the supervision of Yannick Hallez and Martine Meireles
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uniformity, dynamic response, and integration compatibility with modern microelectronic and photonic platforms. The project will combine numerical modelling, optimisation methodologies, and experimental
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Key Responsibilities: The Research Fellow will be in charge of modelling, simulation, and analysis for projects
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and numerical models as well as constitutive model calibration and validation based on physical experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering
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effects, never observed before in an experimental setting, through numerical modelling and laboratory experiments. This PhD thesis is part of a collaboration with the École Normale Supérieure de Lyon and