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their 4th or 5th year of studies (M1, M2 or gap year) - Computer vision skills - Machine learning skills (deep learning, perception models, generative AI…) - Python proficiency in a deep learning framework
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phase-field models require the underlying free-energy density as an input. This internship aims to compute that free-energy landscape from first principles and transfer it to continuum electrode models
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Domaine Physique du noyau, atome, molécule Contrat Post-doctorat Intitulé de l'offre Post-doctorat - HED models development into the ESTHER code and experimental applications - H/F Sujet de stage
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Formal Modeling of Clock Glitch Attacks for Security Verification of Processors H/F Research context Embedded processors are increasingly deployed in security-critical applications, making
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Physics, Applied Mathematics, or Computer Science, with experience in deep generative models (VAE, diffusion) and Python/PyTorch. Applications from statistical physicists are welcome. STILL HESITATING? The
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-performance computing (HPC) and AI systems. You will leverage VPSim (virtual prototyping) and A-DECA (architecture exploration)—tools that enable HW modeling, binary SW execution, functional validation, and
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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