230 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs at CNRS in France
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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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collaboration between the Exa-SofT and the Exa-DI projects and better support multi-linear algebra and tensor contractions in exascale CSE applications and Machine Learning. As part of the collaborative process
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university cafeteria. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7006-JOHSCH-009/Candidater.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research
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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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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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. Location The place of employment and work is the palaeoecological research group of the Department of Environmental Geography, at Toulouse Jean Jaurès University (https://www.univ-tlse2.fr/home/ ), France
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on annotated structures, which could eventually lead to automated comparative grammars. The mission is funded by the ANR Autogramm research project (https://autogramm.github.io/ ). Autogramm focuses on exploring
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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