Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD
-
Smart sanitation technology represents a critical intersection of automation engineering, embedded systems, and global health innovation. With 3.6 billion people worldwide lacking access to safely managed sanitation, automated toilet systems equipped with IoT sensors, intelligent controls, and...
-
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
-
We invite applications for a self-funded PhD to explore innovative research in the development of human-centred embodied multi-agent systems that able to compensate and augment human capabilities in
-
This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
-
This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full
-
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
-
Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA-funded
-
This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum (with fees covered), will deliver a comprehensive understanding of micropollutant removal in different types of nature
-
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