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metascintillator prototypes towards clinical application. The research will combine experimental surface engineering, advanced materials characterisation (SEM, XRD, spectroscopy), and performance testing alongside
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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for ToF-PET and significantly enhancing early cancer diagnostic capabilities. The skills and knowledge gained will be highly transferable to other applications requiring high-performance radiation detection
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policymakers. Entry requirements Applicants should hold or expect to achieve an equivalent of a first or second-class UK honours degree in materials science, physics, engineering, or a related discipline. The
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. At a glance Application deadline26 Nov 2025 Award type(s)PhD Start date26 Jan 2026 Duration of award3 years EligibilityUK, EU, Rest of world Reference numberCRAN-0003 Entry requirements Applicants
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experience align with the research and training programme, followed by questions from the interview panel. At a glance Application deadline10 Sep 2025 Award type(s)PhD Start date20 Oct 2025 Duration of award4
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AI-electronic systems with applications in aerospace, healthcare, and beyond. As AI systems become increasingly integrated into critical applications, ensuring their security and trustworthiness is
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align to the research and training programme, followed by questions from the interview panel. Entry requirements Applicants should have a first or second-class UK honours degree or equivalent in a
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there is a growing revenue from EPSRC, TSB and EU funded work. At a glance Application deadlineOngoing Award type(s)PhD Duration of award3 years EligibilityEU, Rest of world Reference numberCRAN1141 Entry
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at the edge. The project explores advanced topics such as TinyML, neuromorphic design, reconfigurable logic, and autonomous fault recovery, with applications ranging from aerospace, energy, and robotics