34 computer-security-"https:"-"https:"-"https:"-"https:"-"LGEF" PhD positions at The University of Manchester
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. The project will investigate how advanced and modern cryptographic protocols, such as zero-knowledge proofs, secure multiparty computation, homomorphic encryption, exotic signatures, and their post-quantum
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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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the deadline. The project is to contribute to a major Ministry of Defence (MOD) research programme intended to develop generation after next technologies for applications in defence and security, and this
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up to a £5k/annum research training support grant for the full duration of the 4-year programme. Metal-ligand multiple bonding is a burgeoning area for making chemically novel structural motifs
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extreme threats to national security. AWE has pioneered advancements in areas including physics, engineering, materials science, and high-performance computing. Together we’ve helped shape the UK’s
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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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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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Application deadline: All year round Research theme: Computational Mechanics/Applied Mathematics How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students
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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