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structural control for advanced multifunctional applications in electromagnetic shielding and thermal management. The detailed work includes: (1). Establish a precise fabrication methodology to construct long
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), machine learning algorithms, and perception methods can improve the autonomy, robustness, and precision of robotic manipulation in challenging environments. The project lies at the intersection of control
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of an innovative intelligent poultry monitoring platform that combines environmental sensing, bioacoustic monitoring and adaptive lighting control to improve poultry health, welfare and productivity. The technology
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evaluations to explore how interventions operate in practice and how they are experienced by those involved. • Supporting organisations to develop robust internal evaluation capacity, including
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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research environment. Experience: • Prior research experience in one or more of the following areas is desirable: reinforcement learning, robust control, stochastic control, distributionally robust
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modeling results to establish robust process–material–structure relationships and support informed optimization strategies. Support automation, control, and in-process monitoring development for a novel
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that has defeated conventional fabrication approaches. Our platform uses multiphase mircrofluidics to direct programmable protein assembly, followed by mineralisation into robust inorganic frameworks
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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and validation (V&V) strategies for AI-enabled functions, including scenario-based testing, robustness assessment, dataset qualification, fault injection and performance evaluation under off-nominal and