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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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standard operational procedures Ability to follow instructions (evidenced by application) How to apply This is a multi-disciplinary program hence good candidates from chemistry, physics, environmental
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PhD Studentship: Gas Transport in Polymeric Materials for Defence Applications The sustainable use of polymeric materials is underpinned by ensuring long service life in all industries and
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scintillators to X-rays and gamma rays using radioisotopes and X-ray generators. The student will be registered on the Physics PhD program; however, the nature of this research project is highly multi
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meaningful, accessible and co-produced with the communities it aims to benefit. Dissemination will include communication with families and stakeholders as well as academic publications and conference
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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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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning