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Field
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16 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire des Signaux et Systèmes Research Field Engineering Computer science Mathematics Researcher Profile First Stage Researcher
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 days ago
15 Apr 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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synchronization, distributed metrology, and distributed quantum computing. Terrestrial networks (fibers, quantum repeaters) provide a backbone but remain limited by attenuation. The integration of satellite links
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project explores the three-dimensional structure
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Plant species distribution models (SDMs
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generalized parton distributions (GPDs). A key component of the PhD will also involve the development of novel algorithms designed to overcome current computational and theoretical challenges in hadron
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
data compression in physics simulations (communication/computation time/cost, quality of the solution...). The benchmark will be realized with benchopt [3] and will benefit from the distributed coding
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) Established Researcher (R3) Application Deadline 14 Jun 2026 - 22:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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. Chan, “When edge meets learning: Adaptive control for resource- constrained distributed machine learning,” in IEEE INFOCOM 2018- IEEE conference on computer communications. IEEE, 2018, pp. 63– 71. [3] G
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inference, and computational physics. Among generative methods, Normalizing Flows (NF) stand out for their ability to learn a transformation from a simple distribution to a target distribution through a