Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Manchester
- University of Nottingham
- AALTO UNIVERSITY
- ; Swansea University
- KINGS COLLEGE LONDON
- ;
- ; Cranfield University
- ; Loughborough University
- ; The University of Edinburgh
- ; The University of Manchester
- ; University of Exeter
- ; University of Southampton
- Imperial College London
- University of Cambridge
- University of Newcastle
- ; Aston University
- ; Newcastle University
- ; University of Birmingham
- ; University of Cambridge
- ; University of Nottingham
- ; University of Sheffield
- ; University of Strathclyde
- Newcastle University
- The University of Manchester
- UCL
- UNIVERSITY OF VIENNA
- University of Birmingham
- University of Bristol
- University of Cambridge;
- University of Exeter;
- University of Greenwich
- University of Sheffield
- University of Strathclyde;
- University of Surrey
- University of Warwick;
- 26 more »
- « less
-
Field
-
relevance. A digital twin framework for safe, simulation-based validation before deployment in operational wind farms. Develop explainable AI (XAI) frameworks and human-computer interfaces that enable wind
-
, 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
-
simulation study of light matter interaction, digital twin enabled process development and life cycle assessment will be researched. Opens: Immediately Deadline: 08/08/2025. Duration: 36 months Funding: Funded
-
- skills – experience: analytical skills, ability to demonstrate good knowledge in system modelling – simulation, (classical or modern) control theories or control applications with evidence Desirable
-
the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
-
the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
-
thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
-
, including a high level of English language proficiency. Candidates should satisfy the selection criteria set out by CSC Application procedure Please submit your application via The University
-
components with applications in the transport, catalysis and bioengineering industries. The research will focus on wet chemical processes and the study of chemical reactions on the component's surface. We will
-
signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing