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scattering with computer modelling such as molecular dynamics simulations and AI-assisted data mining. The new technical capabilities will help bridge the current gap in biocide development, i.e., to link
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climate impact. Moreover, emissions from aircraft significantly degrade air quality, resulting in approximately 16,000 premature deaths each year. Given the anticipated increase in air traffic, the aviation
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., blockchains), AI safety, and privacy, with potential impact across domains such as finance and healthcare. Applicants are expected to have an MSc degree in computer science or other majors related
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energy? This PhD offers a rewarding chance to become a materials science expert, combining cutting-edge characterisation with real-world industrial impact. At the University of Manchester, working in
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-treatment facilities, and biorefineries. Feedstock choice, regional dynamics, and process side-streams all affect costs, energy use, and emissions. This PhD project will develop advanced computational models
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mechanical fatigue—individually and sequentially, followed by electrical breakdown testing to assess their impact on the dielectric performance of the material subsystems. The target is to develop a
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collaboration with Innospec, aims to investigate how different catalysts influence CNT growth, structure, and performance. Specifically, the study will compare different CNT catalysts, evaluating their impact on
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of Manchester has been at the centre of discovery for the past 200 years, and, as we look forward, our researchers will continue to pursue solutions to the most pressing global challenges that affect our world
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-free stipend based on the UKVI amount (£20,780 for 2025-26). We expect the stipend to increase each year. This studentship is related to a multi-institutional EPSRC Programme Grant “AMFaces: Advanced
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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation and signal processing methods using machine learning techniques to enhance the resilience,...