23 evolution-"https:"-"https:"-"https:"-"Keele-University" positions at Newcastle University
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PhD Studentship: Development of a robust hydrological modelling framework for drought risk assessments Award Summary Tax-free annual living allowance £26,546 a £20,000 research training grant and
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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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stormwater) are a sustainable solution, but their long-term performance often suffers due to generic design approaches that overlook plant ecology and the interaction with soil structure development. This PhD
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approaches that overlook plant ecology and the interaction with soil structure development. This PhD project will transform rain garden design by linking plant traits to hydrological and ecological outcomes
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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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. Methodology The PhD will be divided into 3 work packages (WP): WP1 - Digital Twin Development: This WP focuses on building physics-informed digital twins for high-impact use cases: Smart Grids (simulating load
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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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living examples of a highly skilled workforce delivering an equitable energy transition so that Net Zero is inclusive for all. The development of deep geothermal energy systems relies on robust modelling