119 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
- Grenoble INP - Institute of Engineering
- IMT Mines Ales
- Institut Pasteur
- Nature Careers
- Arts et Métiers Institute of Technology (ENSAM)
- Ecole Normale Supérieure de Lyon
- IFP Energies nouvelles (IFPEN)
- IMT Atlantique
- Universite de Montpellier
- Université Claude Bernard Lyon 1
- Université de Bordeaux / University of Bordeaux
- Université de Strasbourg
- Aix-Marseille Université / CNRS
- Bioptimus
- CEA-Saclay
- Centre de recherche en Automatique de Nancy
- ESRF - European Synchrotron Radiation Facility
- Ecole Normale Supérieure
- European Synchrotron Radiation Facility
- Fondation Nationale des Sciences Politiques
- Grenoble INP - LCIS
- IMT - Atlantique
- IMT Mines Albi
- INSA Strasbourg
- Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP)
- Institute of Image-Guided Surgery of Strasbourg
- Nantes Université
- Télécom Paris
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- Universite Grenoble Alpes
- University Paul Sabatier
- University of Avignon
- University of Strasbourg
- Université Bourgogne Europe
- Université Grenoble Alpes
- Université Savoie Mont Blanc
- Université Sorbonne Paris Nord
- Université de Caen Normandie
- l'institut du thorax, INSERM, CNRS, Nantes Université
- université Strasbourg
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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
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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 5 hours ago
-PULSE addresses a key open question in responsible AI: can we design practical machine learning systems that satisfy strong privacy guarantees [1] and fairness [2] constraints simultaneously, without
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/15 11:59PM (posted 2025/11/04, listed until 2026/05/04) Position Description: Apply Position
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active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 4 days ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets
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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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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 5 days ago
machine learning, 3D visualisation and real-time images (augmented reality). The main robot will the Tiago++, by PAL Robotics, which is a modern omnidirectlonal, bimanual robot. With the help of a PhD