392 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" "Mines Paris PSL" positions at CNRS
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benefit from CNRS employee benefits (meals, vacation, and RTT, etc.). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR9002-FRAMAR-009/Default.aspx Requirements Research FieldChemistryEducation
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environment (Physics, Biology, Engineering). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7288-AUDBAR-077/Default.aspx Requirements Research FieldBiological sciencesEducation LevelPhD
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Postdoctoral position (M/F) on impedance and dielectric study of solid/solid interfaces in batteries
resistances. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8182-SYLFRA-001/Default.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
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https://emploi.cnrs.fr/Offres/Doctorant/UMR8523-ARNMUS-007/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research
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: interferons alpha, lambda, cross-presentation https://institutcochin.fr/projet-6-cellules-dendritiques-contre-vih-int… . The group is expert in studying interactions between human DC and HIV-infected cell
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), Ryoji Shinya (Meiji University, Japan). Background: Mignerot et al. 2024 https://doi.org/10.7554/eLife.88253.2 Kanzaki et al. 2021 https://doi.org/10.1038/s41598-021-95863-1 Our team (http://ibv.unice.fr
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e.g., ultra-cold gases of bosonic or fermionic atoms, machine learning technologies and quantum computing. At the same time, we work in close connection with IJCLab experimentalists, particularly
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support machine learning applications for analyzing electron microscopy images of nanoalloys. Model interactions between nanoalloys and carbon substrates to reflect experimental conditions, incorporating
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the Swiss team led by Christophe Ballif (EPFL/CSEM). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9006-JEAGUI0-017/Default.aspx Requirements Research FieldEngineeringEducation LevelPhD
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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform