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machine structures, together with AI-driven optimization frameworks for diverse applications while considering LCA metrics. The success of this project could serve as a model for other energy-related
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store energy by exploiting quantum phenomena (for example, by exploiting entanglement) in order to improve the performance of the device. There are still many questions surrounding the optimal
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in an optimal way, an issue that will be prominent in industrial, commercial and residential areas across the country. The models and solutions will be developed in a general way in order to be
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, complexity, and harsh operating conditions. This PhD research addresses two critical challenges in this domain: (1) optimizing sensor movement for inspecting large and complex equipment using robots and
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and
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(Dr Jun Jiang) (2) In-situ formability, microstructure analysis and forming process optimization (Prof Li-Liang Wang) (3) Crystal plasticity modelling to understand how microstructural features caused
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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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based at the Department of Obstetrics and Gynaecology, University of Cambridge. They investigate the mechanisms by which sub-optimal nutrition in early life can affect reproductive ageing, the impact of
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workshops as a means to continuously improve technical and theoretical knowledge. Ability to obtain information from literature and from colleagues and integrate this into developing and optimizing work
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research which combined efficient optimization and sequential reliability assessment. The project is funded through an EPSRC call to accelerate research outcomes to achieve a prosperous net-zero and is