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this PhD project at TU Delft, you will develop distributed computational methods for game-theoretic control and optimization to address these challenges. As part of the European Research Council (ERC)-funded
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, they have the potential to solve certain computational problems far more efficiently than classical machines. Realizing this potential requires entirely new numerical algorithms that combine advances in
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, you will focus on developing mathematical models and numerical algorithms that systematically integrate uncertainties into the design process of optical systems. The goal is to enable novel design
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of compute processors. Today’s AI compute processors have multi-Terabit/s interfaces to share intermediate data for distributed training and processing, generating large traffic flows. Low and deterministic
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and
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ones for different stakeholder groups, as a basis for policy making? Are you interested in spatial optimization algorithms and uncertainty assessment? Then this PhD position at the Department of Human
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interfaces to share intermediate data for distributed training and processing, generating large traffic flows. Low and deterministic latency will be required for specific application in data centre for AI
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-world environments inevitably face noisy data, distribution shifts, and situations their training never anticipated. Existing machine learning research focuses on limiting the impact of such disturbances
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use, and long-term crop management goals. While several algorithms have shown promising results in energy savings and crop yield, most of these methods have only been tested in simulation, and make use
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of probabilistic and extremal combinatorics, structural graph theory and algorithms. We study problems on discrete structures such as graphs, permutations, posets or set systems using probabilistic, structural and