Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
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
-
level. Successful candidates will teach and supervise students who are serving officers and civil servants in the UK and allied armed forces and partners. There are also opportunities to contribute
-
Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
-
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
-
combines advanced machine learning with medical imaging physics to develop next-generation tools for biomarker extraction and clinical decision support. You will develop innovative generative models using
-
, 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 research
-
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
-
About us The Department of Informatics is looking to appoint a Reader in Computer Vision Education. This is an exciting time to join us as we continue to grow our department and realise our vision
-
contributing to multi-site or international collaborative research programmes, particularly in maternal, perinatal, or population health Experience applying machine learning or AI methods in healthcare research