49 assistant-professor-computer-science-"https:"-"https:"-"https:"-"https:" PhD positions at The University of Manchester in United Kingdom
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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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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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(Mechanical Engineering at UCL) will also collaborate, he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect that the PhD
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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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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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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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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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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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-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