113 machine-learning-"https:" "https:" "https:" "https:" "https:" positions in France
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- CNRS
- Inria, the French national research institute for the digital sciences
- IMT Atlantique
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- Institut Pasteur
- Télécom Paris
- École nationale des ponts et chaussées
- Ecole Centrale de Lyon
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- Grenoble INP - Institute of Engineering
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- Sorbonne Université SIS (Sciences, Ingénierie, Santé)
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- Université Grenoble Alpes
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- CEA-Saclay
- CNRS - Observatoire de Paris-Meudon
- Centrale Supelec
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- Ecole Nationale des Ponts et Chaussées (ENPC)
- Ecole Normale Supérieure
- Ecole Polytechnique
- French National Research Institute for Agriculture, Food, and the Environment (INRAE)
- IMT MINES ALES
- IMT Mines Ales
- INSA Rouen Normandie
- INSA Strasbourg
- INSTITUT MAX VON LAUE - PAUL LANGEVIN
- Institut Agro Rennes-Angers
- LAUM UMR CNRS 6613
- Mines Paris-PSL
- UNIVERSITE D'ORLEANS
- UNIVERSITE LE HAVRE NORMANDIE
- Universite de Montpellier
- University of Rouen Normandy
- University of Strasbourg
- Université Savoie Mont Blanc
- Université Toulouse Capitole
- Université côte d'azur
- Université de Montpellier
- Université de Strasbourg
- fluiidd
- École polytechnique
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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-France 75 005, France [map ] Subject Areas: Statistical Physics Machine Learning Appl Deadline: 2026/01/16 04:59 AM UnitedKingdomTime (posted 2025/11/04 05:00 AM UnitedKingdomTime, listed until 2026/05/05
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, artificial intelligence—and particularly machine learning methods—has become indispensable. Depending on the specialty, processed data may include numerical values, point clouds, text or images, often
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statistical inference, machine learning and population genetics. The expected outcomes include new computational tools for studying B cell evolution, insights into age dependent immune diversity and the
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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% with Laura Cantini’s team and 20% with the Bioinformatics and Biostatistics HUB. Information about the teams : The Machine Learning for Integrative Genomics team : https://research.pasteur.fr/en/team
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to structured programming in C++ and Python - knowledge of linux / unix operating system - fluent knowledge of spoken and written English - fundamental knowlegde of machine learning (and statistics) - good level
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growth methodology based on real-time growth monitoring enabled by advanced in situ characterization tools (RHEED, ellipsometry, curvature measurements, flux monitoring), coupled with machine-learning (ML
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed