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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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. Solid knowledge in cell and structural biology, as well as expertise in sample preparation and 3D electron microscopy image analysis, are required. Holder of a PhD in biology or biophysics, you have
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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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to optimize performances. The postdoc will carry out structural and morphological characterizations (X-ray diffraction, TOF-SIMS, AFM, and microscopy) of the selected superconducting materials. In the second
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on this benchmark. - Write a publication about this benchmark. #Cea List Moyens / Méthodes / Logiciels AI, Deep Neural Network, Computer Vision, Human behavior analysis Profil du candidat Profile - Students in
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include: · Developing simplified 0D thermodynamic and hydrodynamic models for preliminary injector design and sensitivity analysis; · Developing advanced multiphase and multi-species models and performing
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on various installations (laser fs or ns, XFEL, synchrotrons, high pulse power), and developing numerical simulations and analysis tools. In order to develop new models into ESTHER, the candidate will be
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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