47 computer "https:" "https:" "https:" "https:" "U.S" "UCL" "UCL" "UCL" PhD positions at The University of Manchester
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Application deadline: 31/03/2026 Research theme: Biocatalysis and Protein Engineering Centre for Sustainable Synthesis – BioProcess How to apply: https://www.mib.manchester.ac.uk/research/centres
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or search our funding database for specific scholarships, studentships and awards you may be eligible for. To apply, apply at the link: https://uom.link/pgr-apply-2425 . If you need further information
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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: 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: 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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guest exchange (J. Am. Chem. Soc. 2025, 147, 17201 https://doi.org/10.1021/jacs.5c02868 ). It is the aim of this project to use this novel methodology to investigate a range of single crystal-to-single
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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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that you apply early as the advert may be removed before the deadline. This PhD project aims to develop a virtual tabletting laboratory by creating computational models that capture the multiscale mechanics
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Application deadline: All year round Research theme: Computational Mechanics/Applied Mathematics How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students
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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