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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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develop and apply cryo-ET on microalgae from laboratory cultures and field samples. At LPCV, you will contribute to the research themes of the Photosymbiosis team led by Johan Decelle (https
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and numerical modelling; · Experimental thermal or fluid systems; · Scientific programming and data analysis. Experience with absorption systems, ammonia–water mixtures, injectors/ejectors or phase
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representative tests in small-scale batteries. A multidisciplinary team is involved in the project with much excellence and expertise in the topic. An example of a recent related research can be found here: https
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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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Controlling and manipulating quantum information using advanced nanoelectronic technologies represents a major challenge currently undertaken by CEA-LETI and its partners. A key objective of this
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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