432 machine-learning-"https:" "https:" "https:" "UCL" Postdoctoral positions in France
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astroparticle physics, particle physics, and mathematical physics. The cosmology and astroparticle team (https://astrocosmolapth.com ) conducts research on large-scale cosmic structure, microwave and infrared
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' (http://www.quanthic.org ) within the Institut of Chemistry for Life and Health Sciences at Chimie ParisTech -PSL (Paris, France). This work is financed under the ANR ElectroHIP project. Where to apply
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Website https://emploi.cnrs.fr/Candidat/Offre/UMR5521-FLOVIE-003/Candidater.aspx Requirements Research FieldEngineeringEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD or equivalent
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out within the PICMIC group at IP2I in Lyon, under a pre-maturity grant obtained following a patent awarded to Professor I. Laktineh. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5822
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involved and stakeholders interested in the project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8538-PIEBAR-007/Candidater.aspx Requirements Research FieldEnvironmental scienceEducation
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are looking for a motivated postdoc with solid experience in bioinformatics and in machine learning. The position centers on SRPs and LLPS, and the successful candidate will contribute to several ongoing
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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of adult CA1. Computer work Inmed is made up of 11 research teams, 5 platforms, and 3 shared resources, representing a total of 140 people. The agent will be based at the Luminy campus, in the Calanques
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team at the Laboratoire d'Informatique de Grenoble (LIG). GetAlp conducts research in NLP, machine learning, evaluation, and interpretability. The project will be supervised by Maxime Peyrard (CNRS
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
. [9]). We are particularly interested in improving the selection of transmission opportunities (e.g., using precomputed sequences), possibly constructed with machine learning techniques (as in [8]). We