578 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at CNRS in France
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This research will be conducted at CNRS within the Institut de Chimie des Milieux et Matériaux de Poitiers (IC2MP), located at the University of Poitiers, France (https://ic2mp.labo.univ-poitiers.fr/ ). IC2MP is
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will be in contact with other researchers in high-energy theoretical physics and string theory at LPTHE and in the Paris region who are working on related topics. Where to apply Website https
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. This convergence is particularly visible in Saclay's area where a large community of computer scientists is structured around the PIC code Smilei, and where several ultra-high intensity laser facilities
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Biologie Physico-Chimique', located in the center of Paris. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8261-MAUGUI-009/Candidater.aspx Requirements Research FieldChemistryEducation
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proejct ERC TimeNanolive. The laboratory has an on-site culture room and various microscopes for single molecule localization microscopy. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8214
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or Phonetics Basic knowledge of machine learning tools; familiarity with a scripting language Ability to communicate and coordinate with different partners: field linguists, computer scientists, engineers
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strong attention on emotion analysis. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7271-SERVIL-001/Candidater.aspx Requirements Research FieldComputer scienceEducation LevelPhD
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Website https://emploi.cnrs.fr/Candidat/Offre/UMR7258-STECOU-010/Candidater.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears
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) - bibliographic survey (secondary task) - participating in the management of the laboratory (secondary task) Frame of the contract : the LHFA (https://www.lhfa.cnrs.fr/ ) is an Unité Mixte CNRS-Université de
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to conduct his own research projects if the scientific scope is compatible with the ERC ATTRACTE (modulo machine time). This position is funded by the ERC Starting Grant ATTRACTE project (2023-2028, PI: G