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scattering with computer modelling such as molecular dynamics simulations and AI-assisted data mining. The new technical capabilities will help bridge the current gap in biocide development, i.e., to link
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the investigation and realization of improved microwave probe design, data processing, and visualization techniques to provide a robust method of data analysis, flaw characterization and sizing. AI/machine learning
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design using brute force methods by using non-discriminate parameter variations and recently innovative approaches using artificial neural networks (ANNs) are also developed for the prediction
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and signal processing methods using machine learning techniques to enhance the resilience, efficiency, and security of cell-free massive MIMO systems, which are expected to play a key role in next
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-free stipend based on the UKVI amount (£20,780 for 2025-26). We expect the stipend to increase each year. This studentship is related to a multi-institutional EPSRC Programme Grant “AMFaces: Advanced
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vapour deposition (CVD) remains a leading method for CNT synthesis, yet the role of catalyst composition in controlling CNT morphology and purity is still not fully understood. This PhD project, in
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product sizes and enabling direct on-site manufacturing. The successful candidate will explore innovative methods to realize large-scale on-site 3DP by addressing two key technical challenges: 1) How
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for 2024/25). This funding is available for home, EU students. Identifying materials within sealed containers is of interest to the UK’s continuing stewardship of nuclear material. Radiological methods can
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to increase each year. Tuition fees will also be paid. Home students are eligible. A funded PhD studentship is available in the field of computational inorganic chemistry. The project will involve prediction
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Gamesa Renewable Energy R&D team and also undertake an industry placement as part of the PhD programme. To apply, please contact the main supervisor, Dr Chen - lujia.chen@manchester.ac.uk . Please include