30 assistant-professor-computer-"https:"-"https:"-"https:"-"Technical-University-Of-Denmark" PhD positions at The University of Manchester
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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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, specialises in laser-matter interactions of metal additive manufacturing, and the co-supervisor, Professor Paul Mativenga (UoM), has extensive expertise in laser materials processing. Dr Chu Lun Alex Leung
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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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infrastructure. The successful candidate will benefit from access to extensive expertise across The University of Manchester in civil engineering, structural engineering, fire engineering, computational modelling
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under the supervision of Dr Mehrdad Vasheghani Farahani from Department of Chemical Engineering, with co-supervision by Professor Ian Kinloch from Department of Materials. The successful candidate will
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and uncertainty quantification approaches that deliver traceable confidence intervals for model outputs to aid decision making. • Validate the framework using calibrated datasets (including ageing
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facilities. The project will be supervised by Professor Chris Hardacre and Dr Marta Falkowska, with expertise spanning heterogeneous catalysis, reaction engineering, and neutron-based characterisation. Full
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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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-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