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Field
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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5 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Computer science Mathematics » Algorithms
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during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them. The selected candidate would disseminate their research by publishing in top-tiered
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algorithms (convex/nonconvex, stochastic/robust, MPC) for real-time dispatch, frequency regulation, and DER coordination. Integrate data-driven and physics-informed approaches for state estimation, forecasting
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable
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. The project seeks to develop mathematical models for allocation of critical resources during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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-based prediction. This includes instrumenting a high-power APS torch with video and acoustic sensors, developing machine learning algorithms for feature extraction, and building predictive models
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis