Research Associate: Cardiac Medical Image Analysis

Location
London (Central), London (Greater) (GB)
Salary
£38,826 - £45,649 per annum, including London Weighting Allowance
Posted
18 May 2022
End of advertisement period
15 Jun 2022
Ref
046525
Academic Discipline
Life sciences
Contract Type
Fixed Term
Hours
Full Time

Job description

Artificial intelligence (AI), machine learning (ML) and Digital Twins (DTs) 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 cardiac MRI patient data that will be encoded in a DT 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 DTs 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 single hospital visit but develop novel AI/ML methodologies to analyse and interpret longitudinal data recorded over months or years. 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 be based at King’s College London but hybrid working options are available, 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 position would appeal to a candidate with strong software development skills, including:

 

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

2.           Convolutional neural nets

3.           Software development cycles (Github, CI/CD pipelines, Docker,…)

 

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.

 

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

The applicant should ideally have some knowledge and experience of:

1.           Machine learning

2.           Data science

3.           Statistical modelling

4.           Medical imaging

 

Essential criteria

1.        PhD awarded in Mathematics, Engineering or Computer Science or PhD in Mathematics, Engineering or Computer Science near completion.

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 Imaging

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

5.       Knowledge of software development cycles

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