Research Associate: Artificial Intelligence and Digital Twins in Cardiovascular Disease
Artificial intelligence (AI), machine learning (ML) and Digital Twins (DT) have the potential to transform cardiology. We are seeking to appoint a data scientist/engineer to develop and apply state of the art AI methods to benefit patient outcomes at St Thomas’ Hospital and other major London centres for cardiovascular disease. This project will develop and apply state of the art machine learning methods to automatically analyse longitudinal patient data that will be encoded in a digital twin of the patient’s heart, in order to provide doctors with detailed information on the trajectory of heart disease.
The role will require the development, application and refinement of tools to 1) access databases in a manner consistent with patient privacy and data protection regulations, 2) collate relevant information on the status of the patient, 3) analyse the data, and 4) provide reports and derived data on the anatomy and function of the heart back into the clinical databases. This will include analysis of clinical data and medical images to provide geometric models of the heart, as well as analysis of scar, tissue characteristics and perfusion information. These data will be used to develop digital twins of patient hearts to predict trajectories and outcomes in relation to disease status, treatments, and interventions.
Although AI and ML tools have been developed for image analysis and other applications, application to clinical data and workflow requires robust integration and ability to work with a wide variety of cardiovascular diseases. We wish to move beyond conventional analysis of images taken from a hospital to visit but analyse longitudinal data recorded over months or years. This is a critical step in developing digital twins. This project will determine how current tools can be developed and extended to work with clinical workflows and longitudinal data for the benefit of patients.
The role will require the use of databases and development of data analysis methodologies, including regression and classification techniques. This role requires excellent software development skills, including requirement analysis, design, development, testing, and maintenance of different software components. In addition, the role provides the opportunity for research that develops novel methodologies for AI in cardiovascular disease.
The role will be based at King’s College London, in collaboration with clinical teams at St Thomas’ Hospital and will directly with members of the cardiology and radiology research team.
About the Faculty
About the Department of Biomedical Engineering
About the Cardiac ElectroMechanics Research Group
This post will be offered on a fixed-term contract for 2 years
This is a full-time post
The successful applicant will be responsible for developing and integrating tools for clinical and imaging data analysis and reporting, including imaging and statistical modelling for analysing outcomes in relation to imaging biomarkers.
The applicant should ideally have some knowledge and experience of:
- Machine learning
- Data science
- Statistical modelling
- Database programming
The position would appeal to a candidate with strong software development skills, including:
Machine learning packages (Tensorflow, pytorch,…)
Convolutional neural nets
Statistical modelling packages (R, Stata, …)
Experience using software libraries for ML is an advantage but not essential. An interest in cardiac medical imaging is important, but previous experience is not essential. Previous experience with cloud computing services would be useful but not essential.
Strong communication skills are required to work with researchers from other disciplines, such as clinical end-users, and industry collaborators.
The candidate is also expected to:
work in close collaboration with the other members of the research group
work towards the groups open-source software stack
Experience working with interdisciplinary teams of engineers and clinicians will be valued.
A strongly independent applicant is required who will need to work well with inter-disciplinary teams.
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
- PhD awarded in Mathematics, Engineering or Computer Science or PhD in Mathematics, Engineering or Computer Science near completion.
- Undergraduate or higher degree in engineering, applied maths or computer science
- Higher language computer programming
- Scientific / Medical Writing
- Interest in medical imaging
- Ability to work calmly under pressure
- Ability to act on initiative
- General machine learning experience
- Data analysis packages (R, SAS,…)
- Machine learning libraries (Tensorflow, pytorch,…)
- Knowledge of software development cycles
- Cloud computing services (AWS, Docker, Containers)
- Independent and interdisciplinary researcher
This post is subject to Disclosure and Barring Service clearance