414 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at CNRS in France
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Website https://emploi.cnrs.fr/Candidat/Offre/UMR7019-EMMBIG-005/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldChemistryEducation LevelPhD or equivalent
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contributes to tools such as ProVerif and Tamarin. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7503-VERCOR-005/Candidater.aspx Requirements Research FieldComputer scienceEducation LevelPhD
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to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5274-MARANG-018/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
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students, and master's students, supported by 24 engineers, technicians, and administrative staff. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5635-MIKBEC-030/Candidater.aspx Requirements
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proposed by FLI and ALPAO will make it possible to tackle both the problem of speed, and that of spatial scaling in anticipation of the ELT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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scientists working in diverse domains of fundamental and applied Physics. The postdoc will integrate the Condensed Matter group at CPHT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7644
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Aiguier campus in the 9th arrondissement of Marseille. The LCB is composed of 100 staff members divided into 13 teams. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7283-DELLER-106
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modeling of polymeric, reinforced, and porous materials, with strong expertise in large deformations and numerical homogenization. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7649-JULDIA
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) in Paris. It will be co-supervised by Catherine AMIENS, from the LCC's 'Engineering of Metallic Nanoparticles' team (https://www.lcc-toulouse.fr/ en/engineering-of-metal-nanoparticles-team-l/ ) and
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed