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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
between advanced sensing and analysis, enabling fast, reliable, and quantitative damage assessment of impacted composites. This project lies at the intersection of composite materials engineering, impact
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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the subject area and continues to expand its research horizons. It plays a pivotal role in the £65 million Digital Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification
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, as well as our specialist industrial network. The Centre for Defence Engineering and Physical Science at Cranfield University is a world-leading centre for research, education and consultancy on a
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC
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related discipline. This project would suit a candidate with a background in mechanical, control or aerospace engineering, physics, mathematics, or other relevant engineering/science degree. The ideal
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collaboratively within a dynamic team, utilising cutting-edge technology to create low-cost and user-friendly sensors for deployment by citizen scientists. The project will involve co-designing the sensors with
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social-ecological research on perceptions of urban blue space. Despite often appearing to be natural systems, urban blue space is increasingly planned, managed, and engineered. New research is needed
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physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze
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year. Working at the intersection of water engineering, environmental microbiology, robotics, and lifecycle analysis, you will evaluate autonomous underwater skimming robots that minimise energy use in