Research Associate in Patient Specific Cardiac Modelling

London (Greater)
£38,826 - £45,649 per annum, including London Weighting Allowance
17 Jun 2022
End of advertisement period
17 Jul 2022
Academic Discipline
Clinical, Pre-clinical & Health
Job Type
Research Related
Contract Type
Fixed Term
Full Time

Job description

Physics-based computational models of the heart are increasingly being used to integrate, interpret, and analyse clinical data to inform patient diagnosis and therapy delivery. At King’s College London and St Thomas’ Hospital we create computational models of patients' cardiovascular system, electrophysiology and mechanics directly from patient data. These classical modelling approaches are complemented with machine learning, artificial intelligence and computational statistics approaches to improve and accelerate model calibration and predictions. 


As part of a European Research Council project, we will create patient specific models as part of a prospective clinical trial to test if simulations can be used to predict optimal therapy and patient outcomes.


Applicants will work across the model creation workflow from raw clinical and diagnostic data through to large scale simulations on national high-performance computing resources. The applicant will work with an interdisciplinary team of mathematicians, software developers, engineers, and cardiologists. The project would suit candidates who are passionate about translating cardiac modelling and simulation into clinical applications. 


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. 


This post will be offered on an a fixed-term contract for 2 years  

This is a full-time  post - 100% full time equivalent


Key responsibilities

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: 


1.            Physics based modelling  

2.            Medical imaging 

3.            Data science  


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


1.      Programming (C++ or equivalent) or scripting (python or equivalent)  

2.      Machine learning packages (Tensorflow, pytorch,…) 

3.      Software development cycles (Github, Docker,…)    


Experience using cardiac modelling and software libraries for ML is an advantage but not essential. An interest in cardiac medical image analysis is desired, but previous 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 is also expected to: 


-        work in close collaboration with the other members of the research group 

-        work towards the group 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 

Essential criteria  

1.      PhD awarded in Mathematics, Engineering or Computer Science* 

2.      Undergraduate or higher degree in engineering, applied maths 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 act on initiative  


Desirable criteria

1.      General machine learning experience 

2.      MATLAB & Python 

3.      Medical Image Analysis 

4.      Machine learning libraries (Tensorflow, pytorch,…) 

5.      Physics based modelling 

6.      Cloud computing services (AWS, Docker, Containers) 

7.      Independent and interdisciplinary researcher 


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.

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