Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Nottingham
- ; The University of Edinburgh
- ; University of Birmingham
- ; University of Sheffield
- ; University of Southampton
- ; University of Warwick
- University of Cambridge
- University of Sheffield
- ; City St George’s, University of London
- ; Cranfield University
- ; Lancaster University
- ; Newcastle University
- ; Swansea University
- ; University of Exeter
- ; University of Nottingham
- ; University of Oxford
- ; University of Reading
- AALTO UNIVERSITY
- University of Newcastle
- ; Aston University
- ; Brunel University London
- ; Edge Hill University
- ; Loughborough University
- ; University of Cambridge
- ; University of Greenwich
- ; University of Hertfordshire
- ; University of Plymouth
- ; University of Strathclyde
- ; University of Surrey
- ; University of Sussex
- KINGS COLLEGE LONDON
- University of Manchester
- 25 more »
- « less
-
Field
-
, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation
-
fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
-
fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
-
, process stability, and the downstream consolidation and performance of remanufactured composites. This fully-funded PhD project fits within a wider research programme with industrial partners and an
-
: 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
-
local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
-
modelling tools to understand and tailor the physical and chemical interactions at the interfaces within metascintillators. Cranfield University’s Centre for Materials is internationally recognised
-
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
-
used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
-
. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make