341 evolution "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "St" "St" positions at CNRS in France
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City ST MARTIN D HERES Website https://liphy.univ-grenoble-alpes.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone
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((TERAhertz high-sensitivity thermoelectric detector for SENSing and imaging) contract. Absorbing metasurface is a key device of the thermoelectric detector. Where to apply Website https://emploi.cnrs.fr/Offres
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coupled fibre rings. In this system, light evolves in discrete steps. This kind of evolution leads to nonlinear dynamics that are fundamentally distinct from those in standard photonic lattices, giving rise
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carried out under high voltage at LAAS to demonstrate the advantages of these new devices. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7073-MICPEF-095/Candidater.aspx Requirements
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, ProcédésCountryFranceCityST MARTIN D HERES Contact City ST MARTIN D HERES Website http://simap.grenoble-inp.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail
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accomplish critical functions in inter-cellular communication, controlling tissue development, homeostasis and repair, inflammatory and immune responses, neuronal connectivity, and symbiosis with bacteria
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to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5001-ELSGEN-046/Candidater.aspx Requirements Research FieldEnvironmental scienceEducation LevelPhD or equivalent Research FieldEnvironmental
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the framework of the PEPR Sous-Sol project ORGMET conducted by a consortium of four French laboratories GET, INEEL/ESRF, LFCR and IPREM (https://www.soussol-bien-commun.fr/fr/appel-projets-2024/orgmet
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) The overall following data and analyses of the different physical effects (orbital vs. Spin contribution) will be accompanied by the development of advanced theory/model/numerical simulations and possibly DFT
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained