Chain Florey Post-CCT Transition to Independence Fellowships in Cardiovascu

at  Imperial College London

AVAILABLE DOCUMENTS

Attached documents are available under links. Clicking a document link will initialize its download.

• Download: Chain Florey Post CCT Transition To Independence Fellowship Job Des.Pdf

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.
We reserve the right to close the advert prior to the closing date stated should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.
If you encounter any technical issues while applying online, please don’t hesitate to email us at support.jobs@imperial.ac.uk. We’re here to help.

ABOUT THE ROLE

The Chain Florey Transition-to-Independence (TTI) Fellowship scheme provides a unique opportunity to clinician scientists who have recently completed their clinical training (or will do so in the next 12 months) to develop an intermediate fellowship/clinician scientist research programme with a focus on discovery science and/or early experimental medicine. Drawing on the research strengths of the LMS, the TTI Fellowship addresses an important gap in clinical academic career progression, the challenge clinician scientists face post-CCT when they are no longer eligible for clinical lecturer posts but are not yet competitive for 5-year clinician scientist fellowships awarded by governmental or charitable funders.
The role provides post holders with protected research time (80% research; 20% clinical time for maintenance of competency) to develop a highly competitive application to national governmental and/or charitable funders underpinned by preliminary data. A full mentorship programme will be provided to support the Fellow. This opportunity is aimed at individuals who fulfil the essential requirements listed in the person specification and show outstanding potential to become a leader in clinical translational medicine.

WHAT YOU WOULD BE DOING

The post is part of a BHF-funded Chair in Cardiovascular AI within the Computational Cardiac Imaging Group at the LMS led by Prof Declan O’Regan. The group explores the mechanisms underlying heart disease by applying machine learning and data science techniques to capture complex traits in the heart, across diverse populations, for discovering genetic and environmental determinants of health. The focus of the work is to understand the mechanisms driving diversity in heart disease.
Applicants are required to develop a 1-page project outline, in collaboration with Prof O’Regan, which should be submitted with the application accompanied by a full CV and publication list. The proposal should be focussed on traits derived from human cardiovascular imaging especially in large biobank populations. Any appropriate clinical specialty will be considered.