34 computational-physics-"https:"-"https:"-"https:"-"https:"-"Univ" PhD positions at The University of Manchester
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in Experimental Particle Physics (https://www.hep.manchester.ac.uk/study/ ). Our group (https://www.hep.manchester.ac.uk/ ) is one of the largest research groups in the UK with over 100 members
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Application deadline: All year round Research theme: Applied Mathematics, Computational Metallurgy UK only This 3.5-year PhD project is fully funded and home students are eligible to apply
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2026. We recommend that you apply early as the advert may be removed before the deadline. This PhD project will develop generative hybrid models that integrate AI foundation models with physical
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-wzn23), this project will combine advanced synthetic strategies with reactivity studies, detailed physical characterization and computational studies to elucidate electronic structures. Together
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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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, heat removal, and temperature feedback. This PhD will develop and validate an integrated, computationally efficient modelling workflow for monolithic HPCR systems, coupling deterministic reactor physics
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-value metal production. However, its broader industrial adoption is limited by complex process dynamics, limited process understanding, and the lack of reliable control strategies. The PhD will advance
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their work at major international conferences. Applicants should have a 1st or high 2:1 honours degree (or international equivalent) in mathematics, physics, engineering, computer science or other related
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skills training provided by a mixture of industry and academic project partners covering structural biology; biophysical and analytical methods; computational modelling; directed evolution; process
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of industry and academic project partners covering structural biology; biophysical and analytical methods; computational modelling; directed evolution; process modelling and development; digital skills