Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; Swansea University
- ; The University of Manchester
- ; Loughborough University
- ; University of Warwick
- University of Cambridge
- University of Sheffield
- ; University of Nottingham
- ; University of Southampton
- ; Cranfield University
- ; Newcastle University
- ; University of Bristol
- ; University of Sheffield
- ; University of Birmingham
- ; University of Exeter
- ; University of Leeds
- ; University of Plymouth
- ; University of Surrey
- ; Manchester Metropolitan University
- ; University of Oxford
- ; University of Reading
- ; University of Sussex
- University of Birmingham
- ; Bangor University
- ; University of Bradford
- ; University of Hull
- ; University of Strathclyde
- AALTO UNIVERSITY
- Newcastle University
- ; Anglia Ruskin University
- ; City St George’s, University of London
- ; Coventry University Group
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Imperial College London
- ; King's College London
- ; Queen Mary University of London
- ; Royal Northern College of Music
- ; The University of Edinburgh
- ; UCL
- ; UWE, Bristol
- ; University of Cambridge
- ; University of East Anglia
- ; University of Greenwich
- ; University of Liverpool
- ; University of Portsmouth
- Abertay University
- Aston University
- Heriot Watt University
- Imperial College London
- University of Glasgow
- University of Newcastle
- University of Oxford
- 45 more »
- « less
-
Field
-
computational recourses for limited duration yet highly accurate particle-in-cell (PIC) modelling. Kingston University has developed a simulation model, dubbed PERSEUS, that narrows the gap between these two
-
, into simulation models used for health systems management. The research will provide practical and methodological contributions. The framework will offer healthcare decision-makers better tools for designing
-
Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the Defence Sector (source: the UK Atomic Weapons
-
approaches (e.g. SPG) as well as the use of machine learning, advanced computing, statistical modelling to explore the stochastic response to complex scenarios. This project offers the opportunity to undertake
-
functional studies using primary human tissues and animal models. We apply next-generation sequencing (NGS), long-read technologies (such as Oxford Nanopore), single-cell whole genome sequencing (WGS
-
(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
-
. The student will receive advanced training in quantitative analysis, experimental design, and computational modelling*, and benefit from close collaboration with researchers and policy advocates. The project
-
and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics
-
Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo (School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025
-
Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical