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Description of the offer : The proposed project aims to assess the spin-charge and orbit-charge conversion efficiency of various systems (oxide 2DEGs, Rashba interfaces, etc) using spin-pumping from
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of Computer Science, you will: Lead research in your area of expertise, with a focus on machine learning and foundation models, and have the opportunity to establish and grow your own research group within a
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 1 day ago
recently created team involving researchers from Inria (Rennes, France), Ifremer (Brest) and IMT Atlantique (Brest). Inria is one of the leading research institute in Computer Sciences in France, and Odyssey
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 1 day ago
the Thoth project team (https://thoth.inrialpes.fr/ ) within the Inria Centre at Université Grenoble Alpes (https://www.inria.fr/en/inria-center-universite-grenoble-alpes ) to work under the supervision
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models capable of inferring the IPLS directly from widely available genomic and epigenomic data. Broadly, the project aims to develop integrative approaches at the interface of (epi)genomics, machine
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22 Jul 2026 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering » Computer engineering Researcher Profile First Stage
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develop and implement machine learning approaches to analyze these data and extract relevant indicators to improve water resources management. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant
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degrees: A Master's or engineering degree in robotics, AI, computer science, embedded systems, computer vision, or mechatronics. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR6285-FLOLHO
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two