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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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explore key physical processes governing CO2 plume migration, trapping mechanisms, and fluid–rock interaction under realistic subsurface conditions. The goal is to generate insights that improve the safety
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have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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yield and productivity. Robust yeast and bacterial strains will be studied alongside continuous, integrated fermentation–separation processes to enhance efficiency and reduce fuel costs and lifecycle
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, develop business cases and more. At the 6-month point, students progress onto their interdisciplinary PhD research project, supervised jointly by two academics from two research groups. Usually, supervisors
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persistence arises from the biomass type, formation process and/or the final composition and structure itself. We will quantify these features and engineer biochar with enhanced long-term carbon stability using
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, addressing challenges in (re)manufacturing processes. Motivation The global climate crisis is calling for fundamental transformations in how we design and produce. With advanced robotics technologies
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evidence. - Develop a post-race analysis framework, process, and data toolkit that builds on the historical understanding of race trends to provide immediate feedback to Sport Directors for assessing
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees