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proposal. This PhD will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation on heavily-littered coastlines, in partnership with community groups
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to co-design these avatars and training experiences. The goal is to create digital tools that help new or incoming carers feel better prepared for the specific behaviours, communication styles, and
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research across three core areas of research competence: Circular Economy, Ecological Digital Citizenship, and Robotics & AI. These areas align with the EPSRC Discovery priority of Digital Futures, and the
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the goals of HEHTA, the Living Lab, and the Creative Communities programme. Co-create, build, and maintain a digital engagement platform in collaboration with stakeholders from government, healthcare
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’ families, and community organisations to co-design these avatars and training experiences. The goal is to create digital tools that help new or incoming carers feel better prepared for the specific
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oscillators interacting with body geometry and environment, rather than from centralized digital control. Using a combination of reduced-order models (Hopf/van der Pol/Kuramoto type) and experimental
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research across three core areas of research competence: Circular Economy, Ecological Digital Citizenship, and Robotics & AI. These areas align with the EPSRC Discovery priority of Digital Futures, and the
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PhD: Digital Optimisation of Rail Grinding EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing PhD Research Project Directly Funded UK Students Dr
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advanced technology and business needs, creating smart monitoring systems, predictive maintenance solutions, and digital twins that solve pressing challenges across healthcare, energy, aviation, and
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
time, and enhance safety in aerospace, defence, and automotive sectors. The project contributes to digital engineering and sustainability by improving structural health monitoring and extending component