Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- Newcastle University
- University of Nottingham
- University of East Anglia
- University of Exeter
- Imperial College London;
- University of Exeter;
- The University of Manchester
- University of Cambridge
- Loughborough University
- Swansea University
- The University of Edinburgh;
- UCL
- University of Birmingham;
- University of Cambridge;
- University of Warwick
- Bangor University
- Manchester Metropolitan University
- The University of Manchester;
- University of East Anglia;
- University of Sheffield
- University of Surrey
- ;
- AALTO UNIVERSITY
- Edinburgh Napier University;
- Loughborough University;
- Manchester Metropolitan University;
- Swansea University;
- University of Birmingham
- University of Bradford;
- University of Bristol
- University of Leeds
- University of Nottingham;
- University of Oxford;
- University of Plymouth
- University of Sheffield;
- University of Warwick;
- Abertay University
- City St George’s, University of London
- European Magnetism Association EMA
- KINGS COLLEGE LONDON
- King's College London
- Liverpool John Moores University
- Newcastle University;
- Oxford Brookes University
- The Open University
- The University of Edinburgh
- Ulster University
- University of Bristol;
- University of Essex
- University of Hull;
- University of Liverpool
- University of Liverpool;
- University of Oxford
- University of Plymouth;
- University of Reading
- University of Surrey;
- University of York;
- 48 more »
- « less
-
Field
-
, Cryptocurrencies and Machine Learning Why Choose Us? World-class Faculty: Learn from leading experts with publications in top-tier journals State-of-the-Art Facilities: Benefit from access to our bespoke dealing
-
programming skills. Expertise in developing computer vision and machine learning algorithms would be desirable, highly motivated and enthusiastic about advancing AI for societal impact. Qualifications A high
-
aspects of machine learning. Applications include improving the efficiency of data assimilation methods and understanding why and how deep learning works. Applicants should have, or expect to achieve
-
Location: Central Cambridge PhD Studentship - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis
-
Productivity Index (RPI) using observed versus potential productivity modelled with machine learning (https://doi.org/10.1016/j.ecolind.2025.113208 ), this applied geospatial ecology project will study how
-
speed - Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace
-
composites To propagate uncertainty in material behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help
-
Understanding plankton biodiversity and ecosystem change by applying machine learning – A CASE studentship Lead Supervisor (DoS): Professor Abigail McQuatters-Gollop Second Supervisor: Dr Clare
-
computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
-
computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University