Research Fellow in Computational Cardiac Imaging at The University of Edinburgh

Full time – 35 hours per week

Fixed term until 31^st January 2026

The opportunity:

Applications are invited for a Postdoctoral Research Fellow to work on an exciting research project investigating the use of machine learning to identify markers of coronary artery disease on computed tomography imaging. The project aims to investigate the prevalence of coronary artery calcification in national computed tomography datasets, and evaluate its clinical implications by using linkage to other national healthcare datasets. 

The full-time position offers an opportunity to work closely with Dr Michelle Williams (the project’s Principal Investigator) as part of the Edinburgh Computational Cardiovascular Imaging (ECCI) group at the Centre for Cardiovascular Science, University of Edinburgh. 

The Postdoctoral Fellow will be based at the University of Edinburgh’s Centre for Cardiovascular Science, a leading centre combining world leading cardiovascular disease research, state-of-the-art machine learning and health data science research, and a strong interdisciplinary research culture, 

Your skills and attributes for success: 

• Applicants must have completed (or be close to completing) a Ph.D. in an appropriate discipline.
• Have experience of using Python and R for data analysis and/or image analysis.
• Excellent academic record and work ethic.
• Excellent organizational and oral/written communication skills.
• Excellent team working and problem solving abilities.

Application:

To be considered for the position, please submit:

(1) your Curriculum Vitae
(2) a supporting statement (1 page) with details of how you meet the knowledge, skills and experience required for this post

Informal enquiries may be directed to Dr Michelle Williams, Senior Clinical Lecturer (michelle.williams@ed.ac.uk).