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space explosion involved in complex systems. The aim of this PhD project is to develop distributed supervisory controller synthesis techniques that are scalable to practical systems. Current decomposition
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application of the approach is limited by the fact that tools for synthesis cannot always deal with the state space explosion involved in complex systems. The aim of this PhD project is to develop distributed
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energy resources. The expected outcomes include technical advancement of distributed algorithms for managing energy resources at customer premises. The benefits include more resilient, secure, private, and
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, with both academia and industry recognising its importance. Distribution is an integral part of innumerous computer systems, providing them with essential improvements to aspects such as performance and
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the development of meta-optimization techniques that can automatically search for the best algorithm-hardware pair for a given problem. While we have a history of success in optimizing digital
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theory. o SAT, SMT, and CHC solving. o Temporal logic and TLA+. o Distributed algorithms, blockchains, and smart contracts. o Quantum information theory and Markov decision processes. Additional
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. -) SAT, SMT, and CHC solving. -) Temporal logic and TLA+. -) Distributed algorithms, blockchains, and smart contracts. -) Quantum information theory and Markov decision processes. Conditions of employment
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adaptation of the mesh during simulation to resolve and track features in the flow. The focus of your PhD would be on developing novel algorithms to efficiently redistribute and rebalance the parallel
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introduce predictable spatial structuring in bird impacts that scale up to shape ecosystem function. However, multiple climate factors are changing seabird distributions, and humans can further modify where
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algorithms for large-scale or distributed training/Robustness, fairness, and personalization in multi-agent learning/Training efficiency and communication reduction/Distributed training of transformer models