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achieved in fabrications of coupled double-drum resonator networks, financially supported by EU project Chist-ERA NOEMIA and French ANR-MORETOME projects. A simple reservoir computing function and training
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and an international collaborative network. The position will be based at the Laboratoire Ondes et Matière d'Aquitaine (LOMA), Bordeaux, France. Where to apply Website https://emploi.cnrs.fr/Offres/CDD
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models, whilst respecting the specific spatial structure induced by river networks. - Cleaning, structuring and analysing historical long-term monitoring data (approx. 200 sites). - Adaptation and
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needed for wet-bulb temperature retrieval -Co-locating satellite data with ground-based HadISD stations -Running neural networks and finding the architecture best suited to a case study on India
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toxicology. The successful candidate will benefit from access to state-of-the-art facilities for additive manufacturing, cell culture, microscopy and biomaterial characterization, as well as a network of
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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
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to the dissemination of ultra-stable frequency and time references over telecommunication networks. Its optical-fiber network and laser stations also provide an experimental platform for the development of new
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. Opportunities to collaborate with leading experts in molecular computing and DNA-based technologies, in France and Japan. Relevant publications: https://blog.espci.fr/guillaumegines/publications/ The successful
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the simulation of turbulent flows using a tensor network representation of the Navier–Stokes equations. Unlike recent approaches based on tensor networks, which simulate fluid flows in physical space using finite
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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