271 machine-learning-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- Newcastle University
- University of Nottingham
- ;
- University of East Anglia
- University of East Anglia;
- Swansea University
- Imperial College London;
- Manchester Metropolitan University;
- University of Exeter
- Swansea University;
- UNIVERSITY OF VIENNA
- Manchester Metropolitan University
- The University of Edinburgh
- The University of Manchester
- University of Birmingham
- University of Sheffield
- Loughborough University;
- The University of Edinburgh;
- UCL
- University of Reading;
- University of Surrey
- University of Warwick
- Edinburgh Napier University;
- Loughborough University
- Newcastle University;
- The University of Manchester;
- University of Birmingham;
- University of Bradford;
- University of Cambridge
- University of Cambridge;
- University of Exeter;
- University of Leeds
- University of Liverpool;
- Bangor University
- Oxford Brookes University;
- Ulster University
- University of Bristol
- University of Hull
- University of Oxford;
- University of Plymouth
- University of Plymouth;
- University of Surrey;
- University of Warwick;
- AALTO UNIVERSITY
- City St George’s, University of London
- City St George’s, University of London;
- Cranfield University;
- European Magnetism Association EMA
- Imperial College London
- KINGS COLLEGE LONDON
- King's College London
- King's College London;
- Lancaster University
- Liverpool John Moores University
- Nottingham Trent University
- Oxford Brookes University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Society for the Study of Addiction
- The Open University;
- UWE, Bristol;
- University of Glasgow;
- University of Hull;
- University of Leeds;
- University of Liverpool
- University of Nottingham;
- University of Oxford
- University of Salford;
- University of Sheffield;
- University of Sussex;
- University of York;
- 61 more »
- « less
-
Field
-
for REF 2021 - Research Excellence Framework. For more information about our research results and case studies please visit the following link: https://www.exeter.ac.uk/research/ref2021/ Projects Available
-
should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
-
by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
-
INTENSIVE LEARNING ACADEMY FOR INNOVATION IN HEALTH AND SOCIAL CARE The All-Wales Intensive Learning Academy for Innovation in Health and Social Care has been developed to deliver a world-class learning
-
This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
-
and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
-
refinement or a loss of fidelity in critical regions. Machine learning provides a promising route to capture these relationships more systematically by identifying how local geometric features determine the
-
Wales, meaning most paediatric records are handwritten and unstructured. The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create
-
on combining innovative technologies such as remote monitoring, large language models, machine learning, blockchain, and eco-accounting to enhance the efficiency, security, and sustainability of e-bike charging