PhD in Materials Science

We are pleased to announce a self-funded PhD opportunity for Quantitative assessment of damage in composite materials due to high velocity impacts using AI techniques. Composite materials, such as carbon fibre-reinforced polymers (CFRPs), are increasingly adopted in structural applications due to their superior strength-to-weight ratios and fatigue resistance. However, their layered, anisotropic nature makes them susceptible to complex damage modes like delamination, fibre breakage, and matrix cracking, especially under high-velocity impacts from projectiles or debris. Current assessment techniques (e.g., ultrasonic C-scan, X-ray CT, thermography) rely heavily on expert interpretation, are time-consuming, and often fail to detect subsurface or latent damage accurately. Advances in artificial intelligence offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. Cranfield University is uniquely positioned to support this research through its deep expertise in aerospace engineering, composite materials, and applied artificial intelligence. This project will deliver an AI-driven framework for automated detection and quantification of damage in composite materials from high-velocity impacts.