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Autonomous vehicles (AVs) are advancing rapidly, yet their safety assurance remains limited by the opacity of modern AI systems. Current machine learning–based decision pipelines often function as
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Are you fascinated by working at the intersection of physics and synthetic biology? This PhD project offers a unique opportunity to develop autonomous microswimmers, which are bioinspired structures
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
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high frequency ultrasound is one of few technologies able to fully mineralise PFAS. However, PFAS bound to solids (sorbents and soils) create a technical challenge for direct sonolysis. This project will
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, interviews, eye-tracking and behavioural observation, alongside advanced statistical and qualitative analyses. They will work closely with stakeholders and experts by experience to ensure the research is
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to their presence during manufacture and storage. The effect of exposing a material to either of these species is likely to affect its onward behaviour, and data on these processes will support predictive modelling