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international collaborators. The group's interests cover a wide range of areas including extremal and probabilistic combinatorics, combinatorial optimization, graph theory, game theory, algorithmics and geometry
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deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will
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1 Aug 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique théorique et hautes énergies Research Field Computer science Mathematics » Algorithms Researcher Profile
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with Prof. Mauro Maggioni on problems that include: analysis and algorithms on graphs, geometric analysis of high dimensional data sets, dynamic data sets, scientific machine learning, high-dimensional
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parameters that determine energy fluxes and permafrost dynamics using inverse problems techniques. The developed algorithms and methods will be integrated into the LPJmL Dynamic Global Vegetation Model. Close
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mathematical problems and developing new algorithms for mathematical reasoning. Join us at Caltech and contribute to pioneering research that pushes the boundaries of AI and mathematical reasoning. We look
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biology. CBQB is committed to lead major discoveries in disease mechanisms, novel diagnostics and therapeutics, as well as development of devices and algorithms that will improve health, with lasting impact