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Start date: 29/09/2025 This is an exciting opportunity to study for a PhD funded by the EPSRC-funded EnerHy CDT and Sustainable Plastics Solutions. Offering an annual tax-free stipend of £20,780
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Project summary: A PhD student is sought to undertake a project jointly funded by University of Strathclyde and National Manufacturing Institute Scotland project. The project aims at researching a
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, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or pharmaceutical sciences or a closely related subject (BSc/MChem/MSc). Industrial experience
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datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
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, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD project offers a unique opportunity to develop cutting-edge GPEs that combine the safety of solid-state
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epidemiology and machine learning. The scholarship will fund course fees up to the value of home fees*, a tax-free stipend of no less than £20,780 per annum), plus additional support for research expenses
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Teaser summary: Queen’s Business School invites applications for a fully funded, 3.25-year PhD studentship for entry in September 2025 or January 2026, supporting original research proposals from
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This PhD project offers the opportunity to explore a rich and rapidly developing area of research where powerful mathematical ideas unlock exact solutions in quantum physics. Most physical systems