Research Associate: Understanding Heart Form and Function in Congenital Heart Disease, work at KINGS COLLEGE LONDON

job description

Heart defects are the most common type of birth defect. Improvements in the management of complex congenital heart disease have enabled more than 90% of people born with congenital heart disease to survive into young adulthood. In particular, patients with tetralogy of Fallot often require pulmonary valve replacement.

This role will expand the Cardiac Atlas Project ( to a large cohort of patients with Tetralogy of Fallot, and use Cardiac Magnetic Resonance (CMR) exams and other clinical data to derive statistical atlases. shape, biomechanics and electricity. desynchronization. These atlases will be used to test hypotheses, such as the optimal timing for pulmonary valve replacement, and discover clinical biomarkers that predict pulmonary valve replacement outcomes based on variations in ventricular shape, mechanical properties, and electromechanical dyssynchrony. Machine learning methods will be used to generate and analyze statistical shape models.

The role will be based at King’s College London, working with clinical teams at St Thomas’ Hospital and the University of California, San Diego in a project funded by the National Institutes of Health, USA.

This position will be offered on a fixed-term contract until June 30, 2024

This is a full time position

Main responsibilities

The successful candidate will be responsible for the development and integration of clinical and imaging data analysis tools, including statistical modeling for the analysis of results in relation to imaging biomarkers.

The candidate should ideally have knowledge and experience of:

1. Analysis of medical images

2. Data Science

3. Statistical modeling

4. Scientific/technical programming

The position would appeal to a candidate with strong software development skills, including:

1. Machine learning (pytorch, …)

2. Numerical methods (optimization, non-linear equations, finite element analysis,…)

3. Statistical modeling packages (R, Stata, …)

An interest in cardiac mechanics will be helpful, but prior experience is not essential.

Strong communication skills are required to work with researchers from other disciplines, such as clinical end users and industry collaborators.

The candidate must also:

– work closely with other clinical and engineering staff

– contribute to the web services, database and analysis tools of the Atlas project

Experience working with interdisciplinary teams of engineers and clinicians will be appreciated. A highly independent candidate is required who will work well with interdisciplinary teams.

The above list of responsibilities may not be exhaustive and the post holder will be required to undertake the duties and responsibilities reasonably expected within the scope and classification of the post.

Skills, knowledge and experience

Essential criteria

1. Doctorate obtained or nearly completed*

2. Undergraduate or higher degree in engineering, applied mathematics or computer science

3. Higher Language Computer Programming

4. Scientific/medical writing

5. Interest in medical imaging

6. Ability to work calmly under pressure

7. Ability to take initiative

Desirable criteria

1. Knowledge of medical image analysis

2. Machine Learning


4. Experience in data analysis packages (R, SAS,…)

5. Experience in cardiac function analysis

6. Numerical methods

7. Independent and interdisciplinary researcher

*Please note that this is a PhD level position, however applicants who have submitted their thesis and are awaiting their PhD will be considered. In these circumstances, the appointment will be in 5th year, spine 30 with the title of research assistant. Upon confirmation of the PhD award, the job title will change to Research Associate and the salary will increase to Grade 6.