51 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" scholarships at The University of Manchester
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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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on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI
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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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Application deadline: 15/05/2026 Research theme: Biocatalysis How to apply: https://uom.link/pgr-apply-2425 This 4-year PhD studentship is open to Home (UK) and overseas students. The successful
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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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overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid
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, and data-driven analysis. The project will be supported by a strong research environment with experience in concrete behaviour at elevated temperatures, constitutive modelling, and advanced numerical
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its frontier by integrating mechanistic artificial intelligence with robotic additive manufacturing systems to enable intelligent metal processing. The research will develop physics-informed and data
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will