398 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" scholarships in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- University of Nottingham
- The University of Manchester
- Cranfield University
- University of Birmingham
- Newcastle University
- University of Warwick
- University of Oxford
- University of Sheffield
- Loughborough University;
- University of Birmingham;
- ;
- Imperial College London
- University of Cambridge
- Midlands Graduate School Doctoral Training Partnership
- UNIVERSITY OF VIENNA
- University of Exeter
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Manchester;
- University of Bristol
- University of Greenwich
- Manchester Metropolitan University
- Manchester Metropolitan University;
- Swansea University
- University of East Anglia
- University of Leeds
- University of Surrey
- Newcastle University;
- Northeastern University London
- UCL
- University College London
- University of Cambridge;
- University of Exeter;
- University of Manchester
- University of Strathclyde
- King's College London
- Lancaster University
- Oxford Brookes University
- Swansea University;
- The Open University
- UWE, Bristol;
- University of East Anglia;
- University of Oxford;
- University of Strathclyde;
- University of Surrey;
- University of Westminster;
- Midlands Graduate School Doctoral Training Partnership;
- Oxford Brookes University;
- Royal College of Art
- Ulster University
- University of Aberdeen;
- University of Bradford;
- University of Liverpool
- University of Liverpool;
- University of Nottingham;
- University of Sussex
- Abertay University
- Aston University
- Bangor University
- Bangor University;
- Brunel University London
- Brunel University London;
- Cambridge, University of
- Cardiff University;
- City St George’s, University of London
- City St George’s, University of London;
- Coventry University Group;
- Durham University
- Edge Hill University
- Keele University;
- King's College London;
- Loughborough University
- Middlesex University;
- The Open University;
- The University of Edinburgh;
- UCL;
- UWE, Bristol
- University of Dundee;
- University of Essex
- University of Hertfordshire
- University of Leeds;
- University of Leicester;
- University of Sheffield;
- University of Strathclyde (UOS)
- University of Warwick;
- University of Westminster
- University of York;
- jobs.ac.uk
- 77 more »
- « less
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Biology
- Chemistry
- Materials Science
- Mathematics
- Arts and Literature
- Education
- Linguistics
- Science
- Business
- Electrical Engineering
- Law
- Psychology
- Humanities
- Social Sciences
- Sports and Recreation
- Design
- Earth Sciences
- Philosophy
- Physics
- 13 more »
- « less
-
foundation in either machine learning or mathematical/computational neuroscience, demonstrable programming experience (Python/PyTorch), and the curiosity to work across disciplinary boundaries. A background in
-
machine-learning-based surrogate models to accelerate design and control workflows. This PhD studentship would suit candidates with backgrounds or interests in engineering, physics, applied mathematics
-
an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical engineering, computer science & IT
-
using multimodal approaches including advanced imaging, nano-mechanical characterisation and machine learning techniques Developing physics-informed reliability models using experimental datasets
-
physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell@nottingham.ac.uk . Applications
-
for translational biocatalysis, addressing critical needs in the development of sustainable biotechnologies. The programme will equip PhD students with advanced expertise in enzyme science, machine learning, enzyme
-
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
-
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
-
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