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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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in synthetic organic chemistry are particularly encouraged to apply. Any experience in biochemistry will be beneficial, however full training will be provided for the necessary molecular biology and
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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, an important concept within physics, chemistry and biology, but one that lacks a full mathematical understanding. This project will tackle questions relating to universality within the KPZ class of models. Some
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levels of quality. Good interpersonal skills are required to work effectively in a team consisting of PhD students and postdoctoral researchers. To apply, please contact Dr Yuze Huang (yuze.huang
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This is a fully funded project for home students, funded by NTR-Net. The funding will cover tuition fees and provide a tax free (depending on circumstances) stipend based on the UKVI rate (£19, 237 for 2024/25). This funding is available for home, EU students. Identifying materials within sealed...
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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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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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Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation and signal processing methods using machine learning techniques to enhance the resilience,...
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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