Sort by
Refine Your Search
-
Listed
-
Employer
- Cranfield University
- University of Nottingham
- Harper Adams University
- University of Manchester
- ; University of Nottingham
- University of Sheffield
- ;
- ; University of Southampton
- The University of Manchester
- ; Cranfield University
- ; Swansea University
- ; The University of Edinburgh
- ; The University of Manchester
- ; University of Birmingham
- University of Bristol
- ; Aston University
- ; Brunel University London
- ; Loughborough University
- ; University of Bristol
- ; University of Oxford
- ; University of Warwick
- Brunel University London
- Durham University;
- Kingston University
- Loughborough University
- Newcastle University
- Swansea University
- University of Birmingham
- University of Cambridge
- University of Surrey
- University of Warwick
- University of Warwick;
- 22 more »
- « less
-
Field
-
October 2026 start ONLY For January and April starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme at
-
: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
-
on high-income, Western populations. There is no systematic evidence base demonstrating the best means of preventing unrealistic appearance ideals becoming entrenched in global youth. BIRES seeks
-
thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
-
state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material
-
these, and then determine their imaging performance in bespoke optical systems in the visible light range. Applicants should have, or be expected to gain, a high (1st or 2:1) honours degree in Physics or Electrical
-
these, and then determine their imaging performance in bespoke optical systems in the visible light range. Applicants should have, or be expected to gain, a high (1st or 2:1) honours degree in Physics or Electrical
-
computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the research will be the inclusion stochastic elements
-
, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine