229 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" research jobs at CNRS
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: Marine Biodiversity and ecosystem functioning across spatial, temporal, and human scales”. The overall aim of the project is to acquire knowledge of the principles governing the structure, dynamics
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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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: 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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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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of the project MESSENGER: « Can rock-powered Microbial EcoSyStEms provide valuable iNsiGhts into early life and its emERgence? » funded by the PEPR ORIGINS (https://pepr-origins.fr/en/ ) and integration
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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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. 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
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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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aegypti). It comprises 60 staff members across 6 research teams. https://ibmc.cnrs.fr/laboratoire/m3i/ The Institute is easily accessible by bus and tram. The CNRS contributes towards the cost of private
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in