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Fully funded Ph.D. opportunity in Aerospace AI. Sponsored by EPSRC and BAE Systems covering tuition, fees and a bursary of up to £19,569 (tax free) + £7,500 industrial top-up. Combinatory Artificial
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—such as solar arrays, antennae, and habitat frameworks—while minimizing launch mass and deployment complexity. Key objectives include optimizing structural design for deployment efficiency, resilience under
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reactors, can be optimized for N2O mitigation or ultimately complete N2O removal. Overall, the project represents a unique opportunity to engage with the water utility sector with regards to greenhouse gas
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optimise a ‘Digital Twin’ of the Tees estuary to ensure that the NBS are deployed at locations optimal for performance and longevity while operating within the constraints placed upon deployment by other
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process. Address blind inverse problems by defining a network to learn distortion functions from data, informing the optimization in the learning process. Refine optimization and learning strategies
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more adaptable to other chiral systems. Understanding how these two systems can be optimized and integrated, including effective solvent exchange and recovery, is crucial. Efficient solvent management is
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aims to address these inefficiencies by developing innovative technologies for cleaning optimization and water reuse. The research will explore the use of ultraviolet (UV) fluorescence imaging to monitor
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sensors to understand their local surroundings at sea and inform optimal action. To ensure safety requires the ability to reliably detect, image and recognise their environment, in terms of surrounding sea
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. Finally, a set of recommendations and a toolkit will be developed to support the optimization of professional support services for dentists. This research will take a realist approach to develop a programme
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investigate how to optimize the "athlete-equipment-playing environment" interface, integrating state-of-the-art profiling technologies. The research will adopt an individualised sport approach, targeting up