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activities: • Develop a comprehensive model for selected structures, utilizing finite-difference time-domain (FDTD) electromagnetic simulations and iterative algorithms. • Create a physics-based generative
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comparison with predictions from machine learning models • Close collaboration with researchers in charge of machine learning, algorithmic architecture and performance analysis • Contribution to the scientific
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reactiOns) algorithm, developed within the DeSIS research team, which combines experimental measurements and simulated data to improve predictions of secondary particle production cross sections. High-quality
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, contributing to research in the field of artificial learning. The data generated by this doctoral work will be deposited on open archaeological databases (Nakala, Huma-Num, POP, etc.), and the algorithmic code
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4 Jul 2026 Job Information Organisation/Company CNRS Department Institut de recherche en informatique et systèmes aléatoires Research Field Computer science Mathematics » Algorithms Researcher
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23 Jun 2026 Job Information Organisation/Company CNRS Department Heuristique et Diagnostic des Systèmes Complexes Research Field Computer science Mathematics » Algorithms Researcher Profile First
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digital worlds. Its teams explore, design, and develop models and methodsboth physical and algorithmic—as well as new technologies that bridge the real world (matter and living systems), digital data, and
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of algorithmic processing, and bias management. In the field of cultural heritage, the rapid democratization of image and 3D content generators has led to the widespread circulation of visually appealing