44 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at KINGS COLLEGE LONDON
Sort by
Refine Your Search
-
supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
-
and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
-
establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD
-
on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools
-
. We use this expertise to teach the next generation of health professionals and research scientists. Based across Guy’s, St Thomas’ and Waterloo campuses, King’s Denmark Hill, our academic programme of
-
: david.jackson@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/406107/research-assistant/… Requirements Additional Information Work Location(s) Number of offers
-
(Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and
-
methodological training courses and attend international conferences alongside opportunities to publish peer-reviewed articles, contribute to the teaching and learning programmes in the department, and gain
-
at King's, which brings together a unique range of internationally recognised scientists and clinicians from across the School and King’s College London. More information: https://www.kcl.ac.uk/scmms About
-
King's scientists. Many of the research groups were top rated in the last HEFCE Research Assessment Exercise. The Faculty’s students enjoy unrivalled learning opportunities, supported by strong