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into specialized models, still have significant limitations, particularly in accurately attributing interactions to the correct person in dense scenes and discriminating actions in the presence of objects
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, with the longer-term objective of improving the prediction of fast-charging behaviour. Your project will be to build or adapt a machine-learning interatomic potential for lithiated graphite using density
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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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to a continuous latent space within a CEA consortium combining nuclear physics and AI. Durée du contrat (en mois) 24 Description de l'offre How do you predict a material's properties when the number
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and to allow system-of-chiplets architecture exploration; - Determine best architectural parameters in terms of power, performance, area as well as sustainability using A-DECA tool ; - Collaborate
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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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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