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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 12 days ago
, based on the simulated microstructures. The ATALANTE project, of which this PhD is a part, is divided between experimentation, modeling, and commercialization, and brings together five partners: CEMEF
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, and supporting training activities, preferable in health science education or higher education setting. · Management and programming of simulation models highly desirable Preferred License: Yes If yes
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. Teaching skills. Other qualifications: Experience with high-fidelity simulations (DNS, LES). Experience with heat-transfer modeling, especially in complex-geometry flows. Experience with RANS model
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specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work
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methods for multiphase flow models Integrate experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase
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, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty and
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geomatics, spatial modelling and simulation, and model exploration and evaluation (OpenMole platform https://openmole.org/ ). The recruited individual will also work directly with the project's entomologists
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collaborators. The activities will include: • Electromagnetic modeling and numerical simulations (e.g., FDTD, FEM) • Design of metasurface architectures based on dielectric materials available at CRHEA
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with