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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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background in physics, biophysics, biological physics, or bioengineering. This PhD project will primarily focus on experimental research, which will include data analysis and there is scope for modelling
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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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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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/TEM and XRD. In Physics all the requirement equipment for radiation-based characterisation of the materials is available, including X-ray luminescence and radioisotope gamma irradiation