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Research Associate in Calibrating Cardiac Digital Twins at Scale

King's College London - Faculty of Life Sciences & Medicine

Location: London
Salary: £38,826 to £45,649 per annum, including London Weighting Allowance
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 18th November 2021
Closes: 13th December 2021
Job Ref: 036985
 

Contact details: Steven Niederer, steven.niederer@kcl.ac.uk

Location: St. Thomas' Campus

Job description

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 and physics-based models to analyse longitudinal patient data and encode this information within 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) interpret MRI data to measure patient cardiac anatomy, motion and structure, 2) calibration of cohorts of patient models to clinical data, 3) analyse the data, and 4) provide reports and derived data on the anatomy and function of the heart for evaluating and identifying patient disease trajectories. This will include analysis of clinical data and medical images to provide geometric models of the heart, as well as analysis of scar and tissue characteristics. 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 single hospital 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. Simulations will be performed using the cardiac focused CARP software on local and nation high performance computing resources.
 
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 machine learning and computational statistics methods 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 
   http://www.kcl.ac.uk/lsm/index.aspx 
 
About the Department of Biomedical Engineering 
   http://www.kcl.ac.uk/lsm/research/divisions/imaging/index.aspx 
 
About the Cardiac ElectroMechanics Research Group
 
  http://cemrg.com/  
 
This post will be offered on a fixed-term contract for 2 years 
This is a full-time post
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