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: Establish a tailored enzyme panel for site-selective late-stage functionalization of complex NP scaffolds. Optimize biocatalytic reactions to generate a focused library of new NP analogues. Evaluate
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This studentship aims to develop valid and high-fidelity immersive simulations to support the transfer of performance to competitive sporting environments. Immersive simulation is widely used in
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We invite applications for a fully funded PhD studentship (3.5 years) hosted by the University of Birmingham and conducted in collaboration with Siemens and the UK Met Office. This project is ideal
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stability and how these impact cell state changes. Recently, we have demonstrated the profound impact of G-quadruplexes on the transcription of cancer-related genes and in super-enhancer function. At the core
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PhD Studentship: The Role of O-glycosylation of the Stalk Region of the Immunoglobulin Receptor GPVI
of the receptor, but the exact locations of these glycosylation sites and their function are unknown. A recent antibody targeting the stalk region has been documented to have powerful anti-GPVI properties. Aims: We
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for the British Antarctic Survey. This work is also timely as it connects to the NERC ParaChute project which aims to improve the boundary layer parametrization for high-resolution numerical weather prediction. In
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, engineering, and stakeholder perspectives, the project will deliver new insights into the role of sediment in shaping flood risk. Its outcomes will inform asset management strategies, improve sustainability
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Antimicrobial resistance is one of the most serious threats to humans in the 21st century. Understanding antimicrobial resistance mechanisms is pivotal for combating superbugs. Pathogens use many
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to regulate lipid metabolism in hepatocytes and its impairment contributes to fatty liver. Importantly, the role of alternative cellular mechanisms of intracellular cargo degradation like LC3-associated
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027