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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
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network topologies based on distributed MIMO, formerly referred to as cell-free massive MIMO aim to provide spatially homogeneous capacity compared with traditional architectures; however, it also
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is not. To do so, the candidate will come on board the Manta project [3], which is the framework of the nextgen finite element software for computational mechanics at CEA, and the “Laboratoire d’Etudes
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Category Chemistry Contract Internship Job title Stage BAC+5 Internship in Materials Chemistry Engineering for a master's degree H/F Subject Electrochemical characterization of Hybrid Solid Polymer Electrolytes for High-Performance Lithium-Ion Batteries Contract duration (months) 4 Job...