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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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estimated through CFL-type conditions derived from simplified arguments. Some of our investigations have suggested that phase field equations conditions might be very unfavorable since its associated critical
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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...
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skills and a particular talent for computational simulations, as the project involves advanced gyrokinetic modeling and possibly code development. An interest in high-performance computing will be a
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, easily accessible via the CEA's soft mobility program. A unique research environment dedicated to topics with high societal impact. Experience in a cutting-edge field of innovation with strong industrial