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11 Nov 2025 Job Information Organisation/Company CNRS Department Institut des Systèmes Complexes de Paris Île-de-France Research Field Computer science Mathematics » Algorithms Researcher Profile
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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on the development of materials and processes and is divided into two axes. The first axis aims to improve the most promising state of the art cell materials by optimizing their compositions, microstructures and
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by the CNRS, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical
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pressure sensors, allowing them to measure the movements of the fish and detect pressure signatures in their wake. Numerical simulations were developed to predict the hydrodynamic signatures generated by
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) for the high-luminosity phase of the LHC, in particular on its mechanical design, on the generation of the L1 trigger primitives, and on the development of offline reconstruction algorithms. In addition, it is
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on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics
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» Algorithms Researcher Profile First Stage Researcher (R1) Country France Application Deadline 27 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1
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4 Oct 2025 Job Information Organisation/Company CNRS Department Laboratoire d'informatique de modélisation et d'optimisation des systèmes Research Field Computer science Mathematics » Algorithms
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creation of a database for the various pollution sensors with a view to training online (non-embedded) models in the first instance. - Development of a machine learning algorithm based on the study database