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early risk identification. This PhD project aims to design and develop personalised 3D-printed insoles with enhanced offloading performance and integrated sensing capability. The work will explore novel
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to use the most recent advances in AI-guided structural biology to design artificial protein minibinders that are able to bind specifically and inactivate secreted fungal effector proteins. The student
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of the following objectives: Design and development of long dwell-time, distributed signal processing algorithms for improved target detection Design and development of signal processing techniques for enhanced
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systems, providing early detection of adverse events such as infection and inflammation. The project will involve sensor design and modelling, prototype development, electrochemical characterisation, and
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frameworks that can maximise the performance, efficiency, and emissions reduction potential of such new fuels through intelligent design, modelling, and experimental validation. Research Objectives Investigate
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challenge that needs to be overcome. By understanding and controlling how small droplets dissolve and feed the growth of larger ones, we can design systems with finely tuned size, stability, and function
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adapting their energy use, control strategies, and collective behaviours to enhance sustainability. The research aims to design AI-driven control and energy management frameworks that enable self-organising
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aims to design and study advanced porous solids, such as MOFs, COFs, zeolites, carbonaceous materials, etc., for: Selective CO₂ capture and separation from gas streams Adsorption-based cooling and heat
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The global infrastructure landscape is dominated by ageing assets, many of which were not designed with today’s loading and environmental challenges in mind. Extending the service life of existing
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human health. Work with regional and local authorities to design and evaluate interventions aimed at reducing emissions. The outcomes of this research will deliver critical evidence to inform policy