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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the Defence Sector (source: the UK Atomic Weapons
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project, which encompasses 4-6 PhD studentships across 5 research groups, you will be an integral part of a dynamic doctoral cohort. This unique opportunity provides the successful candidate with the chance
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence
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with inflation). Research training and support grant (RTSG) of £3,000 per year. Funding is available for 4 years. Closes: Open until position filled The overarching aim of this project is to find
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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, ensuring stable operation even as system dynamics evolve. Recent advances in Modular Multilevel Converter (MMC) topologies, along with developments in battery and supercapacitor technologies, create new