532 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" research jobs in France
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning
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and optimize their properties for neuromorphic computing through combined electrical and MOKE measurements, and train them to achieve artificial intelligence tasks. - Micromagnetic simulations - machine
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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will join Magali SUZANNE's team, Apoptosis-Dependent Morphogenesis, at the Center for Integrative Biology (CBI). Founded in 2016, the Toulouse Center for Integrative Biology (CBI; http://cbi-toulouse.fr
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preparation platform, SSMIM - Resources provided (equipment, IT, etc.): Computer workstation, binocular magnifying glass, analytical equipment (IRMS mass spectrometer) Where to apply Website https
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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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of scientific and technical potential (PPST) and therefore, in accordance with regulations, requires your arrival to be authorized by the competent authority of the MESR. Where to apply Website https
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standard Python libraries for machine learning, in particular PyTorch. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6072-DAVTSC-008/Default.aspx Work Location(s) Number of offers
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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