Clinical Research Fellow in Fetal Cardiac Imaging
This 3-year post offers an exciting opportunity to join the UK’s first and only fetal cardiac MRI service at the Evelina London Children’s Hospital/St Thomas’ Hospital, along with our university partner King’s College London (KCL). The successful applicant would be supported in pursuing for a higher degree (e.g. PhD) with the School of Biomedical Engineering and Imaging Sciences in KCL as part of their placement, should they wish to do so. The post is therefore ideally suited to a physician trainee with experience in paediatric and/or fetal cardiology who wishes to pursue a career in clinical research.
During the post the fellow will acquire the skills needed to independently acquire and process detailed 3D and 4D ultrasound and MRI images of the fetal heart, brain and placenta. With the support of the senior fellow and other KCL collaborators, these data will then be analysed using advanced machine learning and causal analysis methods as part of £1.3million BHF-funded project examining the link between placental health, congenital heart disease (CHD), and long-term cardiovascular health.
The development of novel 3D fetal cardiac imaging methods MRI at KCL, and their subsequent translation into a clinical service at St Thomas’ in 2019, have gained international recognition for their innovation and scope. The service now sees between 100-150 patients per year referred from around the UK. The successful applicant would have the unique opportunity to participate in the delivery of this service, situated within one of the largest paediatric and fetal cardiology units in Europe, now incorporating St Thomas’ Hospital, King’s College Hospital, and The Royal Brompton Hospital. They would also gain unique insights into the pre- and postnatal physiology of congenital heart disease, cutting edge cardiovascular imaging methods and clinical management of CHD, as well as experience in a highly collaborative and productive academic environment.
This post will be offered on an a fixed-term contract for 36 months (100% full time equivalent).
• Direct acquisition of complex MRI sequences (with appropriate support and training), including the fetal heart and major vessels across a range of fetal cardiac diagnoses
• Data and software post-processing of MRI data with close support of the senior fellow and biomedical engineering colleagues
• Acquisition and post-processing of US data (with appropriate support and training), to include fetal echocardiography and other methods to assess fetal and placental health
• Supervised medical cover for fetal MRI scans
• Liaison with fetal cardiology patients, consultants, cardiac nurse specialists, midwives and other professionals, accepting and assuming a role as part of an interdisciplinary team
• Contemporaneous processing and reports of MRI data with completion of clinical MRI reports for circulation to fetal and paediatric cardiology, including presentation of relevant findings at weekly fetal cardiology MDM meetings
• Developing relationships with national or international professional organisations within the subject field.
• Engage in individual or collaborative research projects and scholarly activities, both internal and external to the University, applying the knowledge acquired to further develop teaching and other activities.
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Skills, knowledge, and experience
1. MBChB or equivalent medical degree
2. Previous experience or involvement with academic research
3. Evidence of excellent clinical communication skills
4. Ability to work sensitively and compassionately with clinical patients with a range of prenatal diagnoses
5. Ability to work with a variety of professionals from different disciplines
6. Basic level of computer literacy
7. Experience working in paediatric and/or fetal cardiology
8. Experience acquiring and processing medical imaging
9. Involvement with previous research publications and/or abstracts
10. Advanced programming skills