Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- University of Oxford;
- Durham University
- University of Manchester
- King's College London
- Queen Mary University of London;
- University of Liverpool
- DURHAM UNIVERSITY
- University of London
- Bournemouth University;
- Durham University;
- Imperial College London;
- Lancaster University
- Leeds Beckett University;
- Royal Holloway, University of London;
- The University of Manchester;
- University of Cambridge
- University of Warwick;
- University of West London
- 9 more »
- « less
-
Field
-
to work and EV car scheme available For more information, please see University of Manchester Benefits . You can also find information on our Flexible and Hybrid working here . We are an open place of
-
, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
-
, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration CfAI is a large research group in the Department of Physics at Durham University
-
. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely related field) with significant post-qualification research experience. You will experience
-
of reactive force field molecular simulations, supervised machine learning techniques and understanding of mass spectrometry techniques. The post is available for 3 years from 1 September 2026. If you are still
-
development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely
-
(Large Language Models, Convolutional Neural Networks, Machine Learning) for analysis and classification of data.
-
towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research will
-
machine learning approaches to investigate the mechanisms underlying GC-biased gene conversion and understand how meiotic recombination shapes human genetic variation and genome evolution. Working closely
-
, Isomap), manifold learning, and machine-learning classifiers to extract neural geometry metrics from both species. Systematically compare behavioural and neural data across mice and humans, identifying