Sort by
Refine Your Search
-
Duration: 3 years 1st Supervisor: Dr Abhijeet Ghadge 2nd Supervisor: Dr Nicky Yates This fully funded PhD studentship sponsored by Cranfield School of Management, offers a tax‑free bursary of up
-
This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
-
, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in collaboration with industry leaders
-
This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
-
performance. Multistatic radar deployments, which produce several bistatic angles, can aid increasing the signal to noise ratio (SNR), increasing drone detectability and increasing the ability to accurately
-
This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
-
increasing relevance today due to its ability to bridge the physical, digital, and social domains. CPSS are integral to the modern world, shaping the development of intelligent systems that respond dynamically
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
, computer vision, and data analysis using industry-standard tools such as Python, MATLAB, and deep learning frameworks. The student will enhance their ability to manage complex, interdisciplinary research
-
This fully-funded PhD research opportunity, supported by EPRSC Doctoral Landscape Awards (DLA) and Cranfield offers a competitive bursary of £22,000 per annum, covering full tuition fees. This PhD
-
This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance