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Research associate

Leicester
University Of Leicester
Research associate
Posted: 11 May
Offer description

About the role

The Division of Cardiovascular Sciences at the University of Leicester is seeking a Research Associate in MRI Physics to join a multidisciplinary team on a full-time, fixed-term basis (3 years, with potential extension to 5 years). The role forms part of the British Heart Foundation Chair of Cardiology award held by Professor Gerry McCann and focuses on the development, optimisation, and clinical translation of advanced cardiovascular MRI techniques. Professor McCann leads the highly successful and diverse CV imaging Research group and has an outstanding record in developing early career scientists in to independent researchers.

The successful applicant will contribute to cutting-edge cardiac diffusion tensor imaging (DTI) research and emerging quantitative imaging biomarkers. Responsibilities include MRI sequence development, optimisation of diffusion tensor imaging protocols, implementation of AI and deep learning approaches for image reconstruction and denoising, and quantitative microstructural phenotyping in cardiovascular disease, focusing on diabetes and heart failure, aortic stenosis, and coronary artery disease. The post holder will work closely with Dr Maryam Afzali and report to Professor Gerry McCann, collaborating with clinicians, radiographers, engineers, and data scientists at the University of Leicester and with national/International collaborators to advance translational cardiovascular research

About you

You will have a PhD in MRI Physics, Medical Physics, Biomedical Engineering, Applied Mathematics, or a related discipline, with strong expertise in MRI physics and advanced imaging techniques. You will have proven analytical problem-solving skills, experience in programming (Python, C++, or MATLAB), and evidence of contributions to peer-reviewed publications or technical outputs.

Experience in cardiovascular MRI, cardiac diffusion tensor imaging, and machine learning or deep learning methods applied to imaging is highly desirable. You will be a collaborative and motivated researcher, capable of working both independently and as part of a multidisciplinary team, with a clear trajectory toward research independence. Excellent written and verbal communication skills are essential, along with a commitment to continuous professional development.

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