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critical infrastructure—are increasingly exposed to cyber-physical attacks and uncertainties. These disturbances induce complex, time-evolving performance degradation that requires tightly integrated
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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systems (industry, medicine, environment) held by PDEs and/or data-driven, computational fluid dynamics for optimisation and control, data science, automatic learning and uncertainty quantification, offline
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, an uncertainty that contributes to the systematic uncertainty in electroweak asymmetry measurements. Furthermore, they can be used to directly measure beam energy with an accuracy of the order of 10-4
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-physical systems secure and resilient in the presence of uncertainty and cyber-physical attacks? Then you may be our next PhD candidate in resilient and learning-based control of cyber-physical systems
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most promising technologies carry uncertainties, from environmental and economic tradeoffs to questions about how they integrate with existing infrastructures, markets, and other elements of the broader
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characterized by increasing systemic disruptions, traditional supply chain management approaches, primarily focused on performance optimization, are no longer sufficient to cope with uncertainty and dynamic
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candidate will be supervised by P.M. Congedo, E. Denimal Goy and Olivier Le Maître, experts in uncertainty quantification methods. The work will be conducted in the Platon team, a joint research group between
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optimization-based network partitioning point to scalable, communication-aware control designs; stochastic MPC and co-design studies demonstrate methods for handling uncertainty and jointly optimizing assets and
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily