Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Oxford
- University of Oxford;
- AALTO UNIVERSITY
- University College Cork
- Durham University
- Queen Mary University of London;
- UNIVERSITY OF VIENNA
- KINGS COLLEGE LONDON
- King's College London
- MAYNOOTH UNIVERSITY
- Nature Careers
- University of Bath
- University of Liverpool
- University of Liverpool;
- University of London
- ;
- Aston University
- Cardiff University
- Imperial College London
- King's College London;
- MUNSTER TECHNOLOGICAL UNIVERSITY
- Plymouth University
- RCSI - Royal College of Surgeons in Ireland
- University of Cambridge;
- University of Canterbury, New Zealand;
- University of Glasgow;
- University of Lincoln
- University of Lincoln;
- 18 more »
- « less
-
Field
-
their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
-
functional genomics, bioinformatics, and machine learning to support the generation, interpretation, and screening of large-scale experimental and computational outputs. The successful candidate will
-
science, engineering, or a related discipline, with significant postdoctoral research experience. The ideal candidate will have strong expertise in computational biology, machine learning, and quantitative analysis
-
machine-learning-based approaches, and to evaluate the thermodynamic costs of quantum operations. You should work effectively as part of a team and engage constructively with collaborators. You will hold a
-
(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
-
developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
-
to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science or statistics. They will bring strong
-
imaging datasets and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image
-
models (mathematical + software) of existing grid operational practices Systematically exploring different formulations of mixed-integer constraints in grid optimisation problems Developing machine
-
in theory of probability and statistics, machine learning, or formal methods. The post is available from 2 March 2026 until 1 March 2028. If you are still awaiting your PhD to be awarded you will be