Sort by
Refine Your Search
-
Employer
- ;
- ; University of Exeter
- ; University of Sheffield
- Cranfield University
- ; Durham University
- ; Cranfield University
- ; City, University of London
- ; Imperial College London
- ; Lancaster University
- ; Loughborough University
- ; Newcastle University
- ; Rosalind Franklin Institute
- ; Swansea University
- ; University of Bedfordshire
- ; University of Birmingham
- ; University of Greenwich
- Swansea University
- 7 more »
- « less
-
Field
-
information and instructions: “Decolonising the pathways between soil science agricultural policy: An exploration of the spatial-temporal linkages between historical soil and land use appraisals and development
-
Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
-
Industry 5.0 goals. Expect impactful insights into advanced technology integration and human expertise, driving sustainability through improved system performance. Students benefit from collaboration
-
stipend of at least £19,237 for 3 years full-time, or pro rata for part-time study. The student would be based in Renewable energy in the Faculty of Environment, Science and Economy at the Penryn Campus in
-
world-leading or internationally excellent in its quality. Every year Cranfield graduates the highest number of postgraduates in engineering and technology in the UK (Source: Higher Education Statistics
-
In a world facing climate crisis, it is vital to develop new ways to mitigate climate change. This project, funded by Origen Carbon Solutions, focuses on the modelling and optimisation of innovative
-
and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For eligible successful applicants, the studentships comprises: An stipend for 3.5 years (currently
-
Location: Department of Computer Science, Streatham Campus, Exeter The University of Exeter’s Department of Computer Science is inviting applications for a PhD studentship funded by the Faculty
-
be tailored. This project aims to explore how combining network modules with diverse properties can be used to create easy to train AI models capable of solving challenging, real-world problems. It
-
and innovative technology development through interdisciplinary collaborations across our scientific research teams. The Franklin has selected a unique suite of techniques where we can push developments