62 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "University of Waterloo" scholarships at The University of Manchester
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nutrients to survive within the human host, combining biochemistry, chemistry, structural biology and microbiology approaches. Tuberculosis (TB), caused by the bacterial pathogen Mycobacterium tuberculosis
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Application deadline: 30/05/2026 How to apply: https://uom.link/pgr-apply-2425 This 4-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free
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Application deadline: 30/06/2026 Research theme: Applied Mathematics, Continuum Mechanics, Nonlinear PDEs How to apply: https://uom.link/pgr-apply-2425 UK only due to funding restrictions. The
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Application deadline: 31/03/2026 Research theme: Nuclear Materials Hoe to apply: https://uom.link/pgr-apply-2425 UK only This 4-year PhD project is fully funded by the Nuclear Decommissioning
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Application deadline: 28/02/2026 Research theme: Metal Organic Frameworks UK only This 3.5 year PhD project is fully funded by the Department of Chemistry (via EPSRC DLA). Home students, and EU
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before the deadline. Computational haemodynamic modelling provides a powerful framework for linking blood flow dynamics with cardiovascular disease, using in silico approaches to systematically study flow
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up to a £5k/annum research training support grant for the full duration of the 4-year programme. Metal-ligand multiple bonding is a burgeoning area for making chemically novel structural motifs
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on precisely defined chemistry, underpinned by measurement of atomic and isotopic composition/distribution with extreme precision e.g. isotopic implants in Quantum Technologies. Investigation of failure
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in porous geological formations. The successful candidate will develop and implement computational models, validate them against experimental or field data where available, and contribute to the design
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty