85 machine-learning "https:" "https:" "CMU Portugal Program FCT" 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
-
from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
-
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
-
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
-
are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
-
. 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
-
(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
-
metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
-
engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
-
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