Cardiac MRI Research Fellow in Artificial Intelligence

Cardiac MRI Research Fellow in Artificial Intelligence
Closing date
Employer: The University of Sheffield (Department of Infection, Immunity and Cardiovascular Disease) Location: Sheffield


Salary: £40,792 – £48,677 per annum. Potential to progress to £54,765 per annum through sustained exceptional contribution. Grade 8.

An opportunity has arisen at the University of Sheffield’s Department of Infection, Immunity and Cardiovascular Disease for a Cardiac MRI Research Fellow as a result of being awarded a Wellcome Trust Digital Innovator Award. The award allows them to develop a machine learning approach to automatically assess cardiovascular disease features on cardiac MRI. The project is led by Dr Andy Swift and Dr Haiping Lu. They are seeking individuals with a radiological background and detailed understanding of cardiac imaging with an understanding or artificial intelligence techniques in medical imaging.

The role will be based in the POLARIS group in the Academic Unit of Radiology. The Academic Unit of Radiology is an active research unit focused on MR imaging. The main research themes of the unit are neuroscience, developmental and pulmonary MRI.

The post will involve cardiac MRI qualitative and quantitative analysis as well as cardiac MRI training and accreditation. The Research Fellow will assemble and manage the cohorts and data and will work towards a higher degree from the research activities. They will evaluate AI technology and will develop an AI prototype. They will be committed to developing further research in clinical neurophysiology.

The post will particularly suit candidates who have a primary medical degree or have an MSc or higher in clinical research methods. Candidates must have a minimum entry level of ST3. It’s essential they have completed FRCR and hold or be eligible to hold a NTN. The applicant must have GMC full registration at the time of appointment and hold a current licence to practice.

Candidates must have completed core training in acute care clinical specialities sufficient for entry into speciality training grade in Radiology. They must have evidence of awards from prior research and must be committed to further research. It’s essential they have experience in teaching undergraduate MBBS students and other research supervision.

Evidence of knowledge of external grant funding bodies and application procedures as well as organisational and time management skills are crucial. The applicant must have the ability to communicate accurately and concisely, verbally and in writing. The ability to work as part of a multi-disciplinary team and proven ability to work in a group productively is essential.

The individual must demonstrate the potential to progress in the speciality.

How to apply?

To apply visit our job pages ( and search for vacancy number: UOS023068.

Contact details

For informal enquiries about this job and the recruiting department, contact: Dr Andy Swift on or on 07877770018. For administration queries and details on the application process, contact the lead recruiter: Jenny Rodgers on or on 0114 2159595.