-
. 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
-
environment, ensuring that research outcomes directly align with future aviation applications. As part of the PhD, you will have opportunities for placement at Airbus. The main impact of this PhD will be
-
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
-
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
-
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
-
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
-
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
-
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
-
include streamlined certification processes, improved system reliability, and reduced downtime, benefiting industries such as aviation, automotive, and medical devices. By aligning with the increasing
-
recovery. Through real-world testing and industry-aligned development cycles, students gain practical experience in resilience modelling, embedded AI diagnostics, and autonomous recovery protocols