353 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD positions in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Nottingham
- The University of Manchester
- Cranfield University
- University of Birmingham
- Newcastle University
- Swansea University
- UNIVERSITY OF VIENNA
- University of Birmingham;
- University of Warwick
- Loughborough University;
- University of Cambridge
- University of Sheffield
- Imperial College London
- University of Cambridge;
- University of Exeter
- University of Surrey
- University of Bristol
- ;
- Manchester Metropolitan University
- Manchester Metropolitan University;
- The University of Manchester;
- University of East Anglia
- King's College London
- The University of Edinburgh
- University of Warwick;
- AALTO UNIVERSITY
- Newcastle University;
- Northeastern University London
- Oxford Brookes University
- Swansea University;
- UWE, Bristol;
- University of East Anglia;
- University of Exeter;
- University of Leeds
- University of Oxford
- City St George’s, University of London;
- Lancaster University
- Oxford Brookes University;
- The Open University
- UCL
- Ulster University
- University College London
- University of Bradford;
- University of Essex
- University of Nottingham;
- University of Surrey;
- University of Westminster;
- Abertay University
- Brunel University
- Brunel University London
- Brunel University London;
- Cardiff University;
- Edge Hill University
- Imperial College London;
- King's College London;
- Loughborough University
- Middlesex University;
- Midlands Graduate School Doctoral Training Partnership
- Royal College of Art
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Edinburgh;
- UCL;
- UWE, Bristol
- University of Bath;
- University of Hertfordshire
- University of Hull
- University of Liverpool
- University of Newcastle
- University of Oxford;
- University of Reading;
- University of Sheffield;
- University of Strathclyde
- University of Strathclyde (UOS)
- University of Strathclyde;
- University of Sussex
- University of Sussex;
- University of Westminster
- University of York;
- jobs.ac.uk
- 69 more »
- « less
-
Field
-
on basic laparoscopic surgery tasks, using data collected under varying network conditions and applying machine learning and time-series modelling to predict delay. The models will be integrated into a real
-
they can reliably, affordably, and fairly support a net-zero energy system. The research will focus on how data-driven and machine-learning-based control can coordinate demand, storage, and local generation
-
experts at University Hospitals Coventry & Warwickshire/NHS Trust. The research will involve emulating laparoscopic surgical tasks using a robotic platform under varying network conditions. Machine learning
-
science and applications. This project aims to develop the required formalism using modern probabilistic and machine-learning approaches, reformulating the problem in terms of conditional probabilities
-
machine learning techniques, you will identify patient subgroups, improve diagnostic accuracy, and develop a biomarker-based clinical decision support system to assist risk stratification and outcome
-
, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning
-
into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
-
feedback using machine learning and control engineering methods. The project will be hosted at the Bristol Robotics Laboratory (BRL), the UK’s largest academic centre for robotics research, with access
-
: This 4 year fully funded studentship is open to applicants with a first-class or upper second-class degree (or equivalent) in Electrical Engineering, Machine Learning, Physics, Data Analytics or other
-
this challenge head on by combining quantum-mechanical calculations with state-of-the-art machine learning (ML) methodologies to explore and optimise the compositional space of complex high-entropy metal oxides