33 computational-physics-"https:"-"https:"-"https:"-"https:"-"Univ" positions at The University of Manchester in United Kingdom
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honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of
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equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of programming experience. How to Apply Applications should be submitted
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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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Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate
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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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, 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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, imaging and diagnostic). However, there is currently no generic, metrology-grounded AI/ML framework that fuses these heterogeneous data with physics-based models to create trustworthy, asset-specific
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remains largely unexplored. Leaving this physical mechanism unresolved prevents an accurate assessment of the loading and therefore fatigue and design requirements, precluding a complete and assessment of
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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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generate high-quality experimental datasets, establish process-structure-property relationships, and demonstrate ML-guided optimisation of aerogel electrodes. The outcomes are expected to effectively