Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- ; City St George’s, University of London
- ; 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
- Bangor University
- KINGS COLLEGE LONDON
- The University of Manchester;
- University of Bristol
- University of Newcastle
- University of Surrey
- ; Brunel University London
- ; Coventry University Group
- ; Newcastle University
- ; UCL
- ; University of Leeds
- ; University of Warwick
- Abertay 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 Warwick
- 32 more »
- « less
-
Field
-
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
-
Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
-
Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
-
of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
-
? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity
-
, biology, or a closely related discipline Desirable experience: optics and photonics, AI/machine learning, biology, or biomedical sciences Excellent English, analytical, and problem-solving skills UK
-
modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
-
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
-
filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal