Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- ; The University of Manchester
- University of Nottingham
- ; University of Warwick
- ; City St George’s, University of London
- ; University of Exeter
- ; University of Nottingham
- ; Swansea University
- ; Newcastle University
- ; University of Bristol
- ; University of Leeds
- ; University of Southampton
- ; University of Surrey
- Abertay University
- Imperial College London
- University of Cambridge
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Durham University
- ; Loughborough University
- ; The University of Edinburgh
- ; UCL
- ; UWE, Bristol
- ; University of Copenhagen
- ; University of East Anglia
- ; University of Greenwich
- ; University of Strathclyde
- ; University of Sussex
- AALTO UNIVERSITY
- Harper Adams University
- University of Newcastle
- 23 more »
- « less
-
Field
-
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
-
scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making
-
to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
-
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
-
of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
-
including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
-
, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
-
University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
-
Engineering, and Engineering Management. Students with interests in computational mechanics, optimization design, bioinspired design, sustainability management, machine learning, AI, uncertainty quantification
-
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