Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Nottingham
- University of Warwick;
- The University of Manchester
- University of Birmingham
- University of Exeter
- Manchester Metropolitan University
- University of Warwick
- AALTO UNIVERSITY
- Durham University
- Newcastle University
- UNIVERSITY OF VIENNA
- University of Bedfordshire
- University of Cambridge
- University of Cambridge;
- University of Newcastle
- University of Oxford
- University of Sheffield
- Abertay University
- City St George’s, University of London
- Harper Adams University
- King's College London
- King's College London;
- LIVERPOOL JOHN MOORES UNIVERSITY
- Manchester Metropolitan University;
- Oxford Brookes University
- The Rosalind Franklin Institute
- University of Birmingham;
- University of Bristol
- University of Plymouth
- University of Salford
- University of Sheffield;
- University of Sussex
- 22 more »
- « less
-
Field
-
on the responsible use of Research Metrics. Click here for a self-study e-learning module on the Responsible Use of Research Metrics. Key Accountabilities Research Assistant Collect, analyse and interpret research
-
, biomedical engineering, advanced image processing and machine learning. The studentship suits a candidate with a strong background in optometry, physics, engineering, computer science or a related discipline
-
Campylobacter disease burden is assessed, identify drivers of change and possible interventions. You will explore how genomic diversity relates to clinical outcomes, whether machine‑learning approaches can
-
motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
-
heterogeneity govern transport dynamics and degradation mechanisms during extended operation. A coupled mechanical–transport framework, accelerated through machine-learning surrogate models trained on multiscale
-
health. Successful candidates may have experience in electron or X-ray microscopy, image analysis, AI and machine learning, quantitative data science or computational modelling. They will be able to work
-
, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
-
simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
-
, Machine Learning, or Smart Energy Publication record in peer-reviewed journals or conferences, commensurate with stage of career Good programming skills in Python, R, Java, or Matlab Experience
-
modelling, machine learning, or microfluidics. They will also have excellent communication, organisational and problem-solving skills, and a strong interest in interdisciplinary quantitative biology