Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- AALTO UNIVERSITY
- ; City St George’s, University of London
- Imperial College London
- University of Oxford
- University of Oxford;
- University of Sheffield
- University of Warwick
- Harper Adams University
- Royal College of Art
- The University of Edinburgh
- University of Bristol
- University of East Anglia
- University of Exeter
- University of Surrey
- 6 more »
- « less
-
Field
-
PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
-
PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
-
One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
mechanics, and artificial intelligence (AI)—specifically in the domains of non-destructive evaluation (NDE), computer vision, and machine learning. It addresses a critical challenge in the structural health
-
Mission-Inspired priorities of Engineering Net Zero and Artificial Intelligence. This vision also reflects RCA’s institutional research priorities: Climate Crisis and the Circular Economy, and Design & AI
-
combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
-
/Environmental Sciences, Natural Sciences, Artificial Intelligence or a related subject. Mode of Study Full-time Start Date 1 October 2026 Funding Information Note – use this field to provide related salary info
-
in the area of economic inequality. The desired candidates should contribute to research in one of three areas: (1) use of LLMs and incorporation of artificial intelligence into inequality research, (2
-
in the area of economic inequality. The desired candidates should contribute to research in one of three areas: (1) use of LLMs and incorporation of artificial intelligence into inequality research, (2
-
challenge models, vaccine development and evaluation, laboratory science at the interface with artificial intelligence, with superb opportunity for career progression in a stimulating academic environment at