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Field
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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, valuable for laboratory and short-term field studies, into a fully integrated system for real-world deployment, where rapid detection of water quality deterioration is critical. The proposed research will
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mycobacterial infections. The student will characterise their mechanisms of action using cross-linking mass spectrometry and assess their effects on mycobacterial membrane integrity and cell wall metabolism
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on recent advances in recombinant RNAP production, cryo-EM structural elucidation, and fragment-based screening, the project will integrate fluorine-based NMR spectroscopy with active learning algorithms and
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regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue networks perform well across UK towns and
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species capable of efficiently converting mixed C5/C6 sugars into higher alcohols with excellent yield and productivity. Robust yeast and bacterial strains will be studied alongside continuous, integrated
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paired with digital signatures provide confidentiality, integrity and authenticity. Nevertheless, the various functionalities offered by information technology services require more advanced protocols such
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that can deliver complex, high-integrity and scalable reactor components. This PhD project will focus on the engineering of additive manufacturing (AM) to support the design and fabrication of resilient
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fault logs. Apply AI agents by integrating modern communication protocols to ensure reliable data transmission between IoT devices, LLM servers, and data repositories. (3) Machine learning for predictive
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the question ‘how close to failure is the asset?’. By integrating a suite of state-of-the-art sensors and monitoring technologies with data fusion and AI analytics, this research will enable timely