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include streamlined certification processes, improved system reliability, and reduced downtime, benefiting industries such as aviation, automotive, and medical devices. By aligning with the increasing
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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increasingly important. The aim of the project is to explore the collaborative dynamics of agents within eCPS, with a specific focus on aligning their behaviours towards achieving sustainability goals. Cranfield
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recovery. Through real-world testing and industry-aligned development cycles, students gain practical experience in resilience modelling, embedded AI diagnostics, and autonomous recovery protocols
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient