Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Nottingham
- Nature Careers
- University of Birmingham
- ;
- King's College London
- University of Stirling
- Imperial College London
- KINGS COLLEGE LONDON
- University of Sheffield
- ; University of Glasgow
- CRANFIELD UNIVERSITY
- Cranfield University
- Manchester Metropolitan University
- University of London
- University of Manchester
- 5 more »
- « less
-
Field
-
the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
-
of Life Sciences & Medicine. Department: Res Dept of Cardiovascular Imaging. Contact details:Ramesh Valapil. ramesh.valapil@kcl.ac.uk Location: St Thomas Hospital. Category: Research. About Us
-
Resonance (NMR) Experience with experimental NMR techniques and methods for imaging and spectroscopy and an ability to contribute to developing new methods Experience in pulse programme design desirable
-
image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary research. About the Role The role includes carrying out fundamental plant science research related to a
-
image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary research. About the Role The role includes carrying out fundamental plant science research related to a
-
Job id: 118107. Salary: £36,616 - £61,825 pro rata per annum, including London Weighting Allowance. Posted: 20 June 2025. Closing date: 29 June 2025. Business unit: Faculty of Life Sciences
-
position that can be applied across a broad range of industrial sectors, bringing the benefits of passive linear optical superresolution to the domain of in-process control for additive manufacturing
-
passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
-
position that can be applied across a broad range of industrial sectors, bringing the benefits of passive linear optical superresolution to the domain of in-process control for additive manufacturing
-
. They will work on developing novel computer vision methods to improve decision making. The project will provide an opportunity to collaboratively work with computational scientists, pathologists and clinical