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on signals and complex systems. Gipsa-lab develops projects in the strategic fields of energy, the environment, communication, intelligent systems, life and health technologies, and language engineering
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, optimal transport, set evolution and shape optimization, calculus of variations), and/or convex/non-convex optimization methods (first-order algorithms, nonlinear/non-Euclidean gradient descents
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remains largely unexplored and represents a fascinating frontier for molecular computing. The development of new methods will be necessary to enable the manipulation of data within complex molecular
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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The postdoctoral researcher will develop a novel active remote sensing method for the detection and characterization of stratospheric aerosols by adapting the AEROTYPro/GRASP methodology to observations from
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16 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire lorrain de recherche en informatique et ses applications Research Field Computer science Mathematics » Algorithms
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Chemistry for Health” track. IJCLab bases its recruitment policy on the promotion of equality, diversity, and inclusion. These core values support both the professional development of staff, key contributors
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14 Jul 2026 Job Information Organisation/Company CNRS Department Centre de Recherche en Informatique de Lens Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage