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on neural networks whose parameters are trained on simulations (SBI — Simulation-Based Inference). The recruited person will work within the ZTF, LSST/DESC and Lazuli collaborations to implement cosmological
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17 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique de l'ENS Research Field Physics Researcher Profile Recognised Researcher (R2) Application Deadline 6 Aug 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per...
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17 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire national des champs magnétiques intenses Research Field Physics Physics » Solid state physics Physics » Surface physics Researcher Profile First Stage Researcher (R1) Application Deadline 6 Aug 2026 - 23:59...
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of the PRCI project entitled LUCAS (Leverage External Data for Enhanced Understanding and Causal Attribution of Anomalies in Water Network Systems). The research activities will be carried out at the Centre de
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information networks, ranging from single-photon transistors and photonic quantum gates to quantum simulation protocols. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9001-KAMBEN-007/Default.aspx
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tools for the processing of signals or images acquired with biomedical sensor networks (cardiology, neurosciences) or in geosciences (seismology and marine ecology), but also in wireless communications
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the context of a PEPR project, in collaboration with eight CNRS and CEA laboratories working on the future of electrical grids. More specifically, it is linked to WP5, dedicated to cybersecurity and network
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potential for covering the growing need for high-precision sensors, both for basic science and for industrial applications. State-of-the-art quantum sensing methods rely on spin defects hosted in three
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to address the deployment limitations of multi-purpose robots in shared environments. Rather than a single monolithic controller, the robot is treated as a network of collaborating semi-autonomous agents (a
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determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer