236 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" research jobs at CNRS
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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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to field sites made possible by a multi-year project supported by the IPEV. The results are likely to have fundamental and applied implications and a strong impact. Where to apply Website https
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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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platforms (nano-XRF imaging, aging test benches, X-ray microtomography, etc.). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5129-MARCLO-108/Candidater.aspx Requirements 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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supervision of Dr. Bajenoff (http://www.ciml.univ-mrs.fr/fr/science/lab-marc-bajenoff/immunobiologie… ). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7280-MARBAJ-024/Candidater.aspx
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on this topic IMN is a joint research unit of 200 people. The recruited researcher (male/female) will join the PMN (Physics of Materials and Nanostructures) team. Where to apply Website https://emploi.cnrs.fr
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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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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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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