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and optimization but lack frameworks to continuously verify AI safety in operational contexts. This project aims to develop a dynamic validation framework for AI systems using high-fidelity digital
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-generation network architectures. The work will contribute to the development of secure, efficient, and scalable communication solutions for 6G systems. The project is particularly suited to candidates with
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analysis, with the aim of understanding how quantum-safe cryptography can be effectively integrated into next-generation network architectures. The work will contribute to the development of secure
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principles. The proposed project will investigate the development of TCRs by studying the impact of geometries and microstructures on the hydrodynamics of reactants in chemical and/or catalytic reactions and
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formation, compromising the enhancements achieved through the use of TC intensification principles. The proposed project will investigate the development of TCRs by studying the impact of geometries and
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(LCMS, NMR) new covalent warheads with suitable reactivity and stability for application to lysine-TCI development in drug discovery. These optimised warheads will be incorporated into known inhibitors
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allowance of £20,780 (2025/26 UKRI rate). Additional project costs will be provided. Overview The project aims to develop a new approach to drug discovery by developing new methods for synthesising and
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that will train the next-generation of doctoral carbon champions who are renowned for research excellence and interdisciplinary systemic thinking for Net Zero. The ReNU+ vision is that they will become
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, what changes are made (e.g., labelling), and how it is used (e.g., which models train on it, which versions, for what purpose). Middleware solutions: In this topic, we will explore middleware solutions
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Overview The project aims to develop a new approach to drug discovery by developing new methods for synthesising and testing potential drug candidates in high-throughput. One of the barriers