-
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
-
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
-
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
-
, 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
-
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
-
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
-
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),...