Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; Swansea University
- ; The University of Manchester
- ; University of Birmingham
- University of Sheffield
- ; University of Southampton
- ; University of Warwick
- ; University of Bristol
- ; University of Surrey
- University of Cambridge
- ; Newcastle University
- ; University of Exeter
- ; City St George’s, University of London
- ; Cranfield University
- ; The University of Edinburgh
- ; University of Nottingham
- ; Loughborough University
- ; University of Sheffield
- Imperial College London
- University of Newcastle
- ; University of Oxford
- AALTO UNIVERSITY
- ; Brunel University London
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; University of Cambridge
- ; University of East Anglia
- ; University of Greenwich
- ; University of Leeds
- ; University of Reading
- ; University of Strathclyde
- Abertay University
- Harper Adams University
- University of Oxford
- ; Aston University
- ; Coventry University Group
- ; Durham University
- ; Imperial College London
- ; Manchester Metropolitan University
- ; Royal Northern College of Music
- ; St George's, University of London
- ; UCL
- ; University of Bradford
- ; University of Plymouth
- ; University of Sussex
- Aston University
- Heriot Watt University
- UNIVERSITY OF VIENNA
- University of Glasgow
- University of Liverpool
- 41 more »
- « less
-
Field
-
) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
-
computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
-
) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
-
November 2025 or as soon as possible thereafter. This PhD project aims to explore how emerging datasets could provide value to the UK’s insurance industry through a combination of data analytics, modelling
-
. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying
-
, multi-source learning is used to integrate diverse patient populations to build robust models, but having to protect sensitive information. Various modern ML paradigms are proposed to address the diverse
-
: 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
-
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
-
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
-
sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data