Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ; City St George’s, University of London
- University of Nottingham
- ; University of Nottingham
- University of Cambridge
- University of Sheffield
- ;
- ; Swansea University
- ; The University of Manchester
- ; University of Exeter
- AALTO UNIVERSITY
- The University of Manchester;
- University of Cambridge;
- ; University of Southampton
- KINGS COLLEGE LONDON
- The University of Manchester
- University of Bristol
- University of Newcastle
- ; Brunel University London
- ; Coventry University Group
- ; Newcastle University
- ; UCL
- ; University of Leeds
- ; University of Warwick
- Abertay University
- Bangor University
- Bangor University;
- Harper Adams University
- King's College London;
- Liverpool John Moores University
- Loughborough University;
- Nature Careers
- Oxford Brookes University
- The University of Edinburgh;
- UCL
- University of Birmingham
- University of Exeter
- University of Liverpool
- University of Nottingham;
- University of Oxford
- University of Sheffield;
- University of Surrey
- University of Surrey;
- University of Warwick
- 34 more »
- « less
-
Field
-
Research theme: "Next Generation Wireless Networks", "Signal Processing", "Machine Learning" UK only How to apply: uom.link/pgr-apply-2425 This PhD project aims to design novel resource allocation
-
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
-
both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate
-
scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
-
Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
-
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
-
filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
-
synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
-
This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
-
for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and