Sort by
Refine Your Search
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
-
Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
-
Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
-
for Security Operations Centres (SOCs) while pioneering strategies for quantum-era resilience. This project sits at the intersection of Artificial Intelligence, Cybersecurity, and Explainable Computing. It
-
second class UK honours degree or equivalent. This project would suit an applicant with a materials science/engineering, mechanical/chemical engineering or chemistry background or a related discipline
-
honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
-
management, and scientific communication. This combination of technical expertise and practical experience will prepare them for leadership roles in academia, aerospace, autonomous systems, telecommunications
-
in radiation–matter interactions, computational modelling, and materials science, with a strong publication record (h-index 36, i10-index 69). Dr Francesco Fanicchia, Research Area Lead: Material
-
pressure to reduce both energy demand and chemical consumption. Project SandSCAPE, an Ofwat-funded programme, tackles this challenge by integrating purpose-built robots that skim slow sand filter beds while
-
relevance. A digital twin framework for safe, simulation-based validation before deployment in operational wind farms. Develop explainable AI (XAI) frameworks and human-computer interfaces that enable wind