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sequencing technologies (such as nanopore sequencing) has enabled the discovery and analysis of complex regions of the genome for the first time. Novel long read sequencing approaches developed in the Ryan
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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