Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; Swansea University
- ; The University of Manchester
- University of Sheffield
- ; University of Southampton
- ; University of Surrey
- ; City St George’s, University of London
- ; University of Birmingham
- ; Loughborough University
- ; Newcastle University
- ; University of Exeter
- AALTO UNIVERSITY
- University of Newcastle
- ; The University of Edinburgh
- ; University of Bristol
- ; University of Nottingham
- ; University of Oxford
- Imperial College London
- University of Bristol
- University of Oxford
- ; Cranfield University
- ; University of Cambridge
- ; University of Sheffield
- ; University of Warwick
- Abertay University
- KINGS COLLEGE LONDON
- The University of Edinburgh
- The University of Manchester
- University of Cambridge
- University of Warwick
- ; Aston University
- ; Brunel University London
- ; Coventry University Group
- ; Durham University
- ; Imperial College London
- ; St George's, University of London
- ; University of East Anglia
- ; University of Greenwich
- ; University of Leeds
- ; University of Plymouth
- ; University of Reading
- ; University of Strathclyde
- Coventry University Group
- Harper Adams University
- Loughborough University
- Manchester Metropolitan University
- Newcastle University
- The University of Manchester;
- UCL
- UNIVERSITY OF VIENNA
- University of Birmingham
- University of Cambridge;
- University of Exeter
- University of Greenwich
- University of Liverpool
- University of London
- University of Nottingham;
- 49 more »
- « less
-
Field
-
28 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country
-
coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
-
Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position
-
structures, and to examine and model the ‘ageing’ effects that take place during long-term storage for space modules that may then be subjected to the space and de-orbit environment. Key tasks will be
-
accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
-
the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
-
Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
-
determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new
-
for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a
-
performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling