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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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We are looking for a co-design engineer for future computing architectures in HPC. This position, in a fixed-term contract, is based at the Nano-Innov site of Paris-Saclay, Essonne (91). As part of
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with a high pulse power device. Another study intends to develop non-thermal electrons distribution which is of trendemous importance for UHI experiments. Durée du contrat (en mois) 2 ans + 2 x 1an
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transport. The work will include: Contributing to the design and upgrade of the existing core reflectometer to enable poloidal correlation measurements; Participating in the implementation of the associated
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, Physical Chemistry, or Electrochemistry. - Knowledge of rechargeable batteries and a solid understanding of the associated scientific and technological challenges are essential. - Knowledge of Organic
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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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Scientific Reports, already cutting computational cost by more than two orders of magnitude (22,282 CPU hours down to 85 on a test case). With no known equivalent in the international literature, PULSE
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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