Research Associate – Artificial Intelligence in Cardiac MRI

Job description

Coronary Artery Disease (CAD) is highly prevalent and represents one of the highest costs to the healthcare system. Cardiac magnetic resonance (CMR) is playing an expanding role in the diagnosis of CAD. However, the lack of sufficient expertise for the interpretation of the CMR images is limiting its wider utilisation. There has been significant research into the use of artificial intelligence (AI) for automated and user-independent CMR analysis but very little of this has made it to clinical practice yet. The aim of this research programme, supported via a Wellcome Trust Innovator Award, is to develop modern deep learning methodologies to overcome the challenge of integrating AI solutions for automated CMR image analysis, robustly, into clinical practice and will build on the group’s experience in quantitative perfusion CMR. 

A particular focus of this position will be on the development of near real-time deep learning models to replace the existing time-consuming processing steps such as image registration and tracer-kinetic modelling, and on improving models robustness to domain shifts. 

The role will be based at King’s College London, in collaboration with clinical teams at St Thomas’ Hospital, as part of the London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare. This project will also collaborate with relevant healthcare industry partners to ensure translation of the methods into clinical practice worldwide.

About the Faculty  

  https://www.kcl.ac.uk/lsm

About the Department of Biomedical Engineering  

  https://www.kcl.ac.uk/bmeis 

About The London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare 

  https://www.aicentre.co.uk

This post will be offered on a full-time, fixed term contract until 30th September 2023.

Key responsibilities

• Develop and integrate deep learning models for automated analysis of cardiac MRI data.  
• Work in close collaboration with clinical colleagues to facilitate clinical validation and adoption of the image analysis methods.
• Attend and present (as appropriate) research findings and papers at internal and external academic meetings, seminars and conferences and to contribute to the internal and external visibility of the Department.  
• Contribute to the production of research reports and publications.  

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

Essential criteria 

1.       Honours degree (2:1 or above) or equivalent in Mathematics, Engineering, Physics, Computer Science or related numerate discipline 

2.       PhD in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering, Physics, Applied Mathematics or other relevant area near completion* 

3.       Competence in machine learning, (medical) image analysis / computer vision. 

4.       Ability to work effectively within a collaborative software development environment with people from a variety of backgrounds. 

5.       Ability to successfully manage tasks to a deadline and to work calmly under pressure.  

6.       strong software development skills (Python), 

7.       Experience including relevant machine learning packages (Tensorflow, Pytorch, …). 

8.       Highly developed verbal and written communication skills (ranging from informal 1:1 discussions, formal presentations covering both oral and written skills), including the ability to liaise with staff at a range of levels internal and external to the organisation. 

Desirable criteria 

1.       Knowledge of medical imaging acquisition principles. 

2.       Experience in (medical) image analysis / computer vision packages  

3.       Experience in standard software engineering practices including version control systems and software testing methodologies. 

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.