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control performance and efficiency. This PhD project focuses on data-driven analysis of confined liquids structure, informed by total neutron scattering. The emphasis is on developing new analysis
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not originally designed to manage large numbers of flexible and decentralised energy resources. This PhD project will develop new AI-driven methods for operating smart distribution networks so that
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. Robotic metal additive manufacturing offers transformative potential for flexible, large-scale, and high
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hazardous precious metal catalysts. Delivered high-performing biocatalysts Engineered industry-ready enzymes suitable for large scale pharmaceutical manufacturing. We’ve also helped shape national policy. In