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. Assess ecological change by applying shotgun metagenomics and amplicon sequencing to track microbial community shifts under persistent wet skimming. Translate lessons learned into engineering design rules
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
a standards-aligned semantic framework to ensure interoperability, reusability, and scalability across systems and sectors •Model system degradation over time by developing temporal knowledge graphs
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additive manufacturing. This project will be closely aligned with the ATI research program (I-Break: Wire-based DED Technology Maturation and Landing Gear Application) and other industrial research projects
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are demonstrated through its extensive MSc and PhD research initiatives and its ongoing technology development programs in large-scale additive manufacturing. This project will be closely aligned with the ATI
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aligned nations may face considerable challenges. Diversity and Inclusion at Cranfield We are committed to fostering equity, diversity, and inclusion in our CDT program, and warmly encourage applications
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environmental sustainability is paramount, this research offers students the chance to contribute to the creation of green technologies that align with global efforts to reduce carbon footprints. Addressing
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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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—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
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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