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Numerical analysis of fully explicit phase-field models for dynamic fracture of materials H/F Numerical analysis of fully explicit phase-field models for dynamic fracture of materials Understanding
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validated. In parallel, CEA-List has developed µArchiFI [3-4], a formal framework enabling pre-silicon analysis of fault injection effects at RTL level, from hardware implementation details up to software
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time-frequency signal processing; Strong Python programming skills for scientific data analysis, including the use of AI-based analysis packages; Good analytical and problem-solving abilities; Excellent
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performance analysis in a fully virtualized environment. These tools integrate QEMU-based emulation, external models, and a Python API for performance data extraction during application execution. A-DECA
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Domaine Mathématiques, information scientifique, logiciel Contrat Post-doctorat Intitulé de l'offre Using generative AI to simulate chemically disordered nuclear materials at the atomic level H/F
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in the training data and can naturally arrive during deployment (i.e., a distribution shift), increasing the risk of obtaining wrong predictions. Consequently, OoD samples detection is crucial in