10 science-"https:"-"https:"-"https:"-"Lunenfeld-Tanenbaum-Research-Institute" positions at CEA in France
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organelles, and macro-complex structures in their cellular context (in situ structural biology). The laboratory Cell and Plant Physiology (LPCV), which aims to understand the adaptive response of microalgae
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an innovative technology through the complete development process: Physical modelling → CFD simulation → prototype development → experimental validation → scientific publications and technological innovation
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, numerical systems designs. The project builds on complementary developments from both teams: TRAITOR for experimental fault injection and µArchiFI for formal securi Applicants should hold a PhD in computer science
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Domaine Mathématiques, information scientifique, logiciel Contrat Stage Intitulé de l'offre Stage Human-Object Interaction benchmarking-Saclay-H/F Sujet de stage The interpretation of human interactions in images or videos has significantly improved with the emergence of Large Language Models...
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project is to achieve the integration of quantum devices within Fully Depleted Silicon-On-Insulator (FD-SOI) technology on a 300 mm platform. The success of this integration critically depends
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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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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 ESTHER is a 1D Lagrangian code for radiation-matter interaction that studies the evolution of...
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tutorials as well as in the valorization of our innovations. #CEA-List ; #researcher ; #Nanotechnology ; #Simulation Model You have an engineering/master's degree or a PhD in the field of computer science
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physics, microwave engineering, electrical engineering, physics or a closely related field. The ideal candidate will have: A solid background in plasma physics and/or microwave diagnostics; Experience in
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The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented in the training data and can naturally arrive during deployment (i.e., a distribution shift),...