Early stage researcher in computational cardiac anatomy: novel shape biomarkers

Reference: THW/17/059639/001334
Salary Details: £30,216 to £33,696 per annum
Contract Type: Temporary/Fixed term
Contract Term: Full time

The management of cardiovascular conditions is in a continuous improvement driven by technological advances. Medical images and sensors present a detailed picture of the anatomy, and also the function, of the heart.

We now have the opportunity to detect the disease in an earlier stage, to risk stratify each patient, and to plan the optimal timing and strategy of the treatment. And computational models of cardiac physiology offer an ideal pathway to seize this opportunity, by integrating all the rich available information into a cohesive picture, and by then allowing an individualised study of the diagnosis and prognosis.

In this context the successful candidate will be integrated in the prestigious ITN training network “Personalised In-silico Cardiology” (PIC), a coordinated doctoral training initiative provided by academic, industrial and clinical partners (http://picnet.eu).

The specific objective of this role is to propose novel clinical diagnostic metrics based on the concept of statistical models of anatomy.

This project will benefit from the huge amount of imaging data stored in health information systems, and build statistical atlases of the cardiac ventricles and main vessels. The description of the range of variability in healthy population will then offer the opportunity to detect earlier deviations caused by disease. The patient-specific and anatomically detailed geometrical models will also be used to run simulations to predict the impact of therapy in heart failure, arrhythmia or valve conditions.

The selection process will include a presentation and a panel interview.

For an informal discussion to find out more about the role please contact Pablo Lamata [Email Address Removed]

To apply for this role, please go to the King’s College London HireWire Job Board
and register to download and submit the specified application form.

Closing date: 18 October 2017