337 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Employer
- University of Nottingham
- The University of Manchester
- Cranfield University
- University of Birmingham
- Newcastle University
- University of Warwick
- University of Sheffield
- Loughborough University;
- University of Birmingham;
- Imperial College London
- University of Cambridge
- UNIVERSITY OF VIENNA
- University of Exeter
- University of Bristol
- ;
- Manchester Metropolitan University
- Manchester Metropolitan University;
- Swansea University
- The University of Manchester;
- University of East Anglia
- University of Surrey
- Newcastle University;
- Northeastern University London
- University of Cambridge;
- University of Leeds
- University of Strathclyde
- King's College London
- Oxford Brookes University
- Swansea University;
- The Open University
- UCL
- UWE, Bristol;
- University of East Anglia;
- University of Exeter;
- University of Strathclyde;
- University of Surrey;
- University of Westminster;
- Lancaster University
- Oxford Brookes University;
- Royal College of Art
- Ulster University
- University College London
- University of Bradford;
- University of Liverpool
- University of Liverpool;
- University of Nottingham;
- University of Sussex
- Abertay University
- Brunel University London;
- Cardiff University;
- City St George’s, University of London
- City St George’s, University of London;
- Edge Hill University
- King's College London;
- Loughborough University
- Middlesex University;
- Midlands Graduate School Doctoral Training Partnership
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The Open University;
- The University of Edinburgh;
- UCL;
- UWE, Bristol
- University of Essex
- University of Hertfordshire
- University of Oxford
- University of Oxford;
- University of Sheffield;
- University of Strathclyde (UOS)
- University of Warwick;
- University of Westminster
- University of York;
- jobs.ac.uk
- 62 more »
- « less
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Biology
- Chemistry
- Materials Science
- Arts and Literature
- Mathematics
- Linguistics
- Electrical Engineering
- Science
- Business
- Psychology
- Law
- Education
- Humanities
- Social Sciences
- Sports and Recreation
- Earth Sciences
- Philosophy
- Physics
- 12 more »
- « less
-
from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
-
requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
-
filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
-
to commence on 1st October 2026 are now open at the School of Physical Sciences. The projects available are listed here: https://www.open.ac.uk/science/physical-science/phd-students/current-phd-studentships
-
bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning
-
, release kinetics under biologically relevant triggers. The successful candidate will work at the interface of organic synthesis, chemical biology, and machine learning to guide linker design and optimise
-
this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
-
Modelling, Applied Statistics, Linguistics, Data Analysis, Large Language Models, Machine Learning. Start date: 1st October 2026 Deadline: 30th April Duration: 36 months Funding: Funded Funding towards
-
data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
-
collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI