46 computer-engineering-"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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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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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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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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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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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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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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workflows and contribute to building UK capability in an important advanced reactor area. The ideal candidate will enjoy computational modelling and quantitative problem‑solving, with a strong foundation in
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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