Research Associate in Translating In-Silico Cardiac Electrophysiology Procedure Guidance System

4 May 2024
Job Information

Organisation/Company

KINGS COLLEGE LONDON

Research Field

Engineering
Computer science
Mathematics
Physics

Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)
Established Researcher (R3)

Country

United Kingdom

Application Deadline

3 May 2025 - 00:00 (UTC)

Type of Contract

Other

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

About us

The successful applicant will be located with the newly created Research Department of Digital Twins (North Wing of St Thomas’ Hospital), primarily supervised by Dr Martin Bishop. The post will benefit from the computational and clinical electrophysiological infrastructure provided by the School of Biomedical Engineering & Imaging Sciences and will be based at St Thomas’ Hospital.

This work will be performed in close collaboration with the clinical researchers at KCL and St Thomas’ Hospital, lead by Dr John Whitaker and Prof Aldo Rinaldi. The project is also in direct collaboration with Prof Gernot Plank (Medical University of Graz) and the cardiac software and solutions company NumeriCor working with Dr Aurel Neic.

About the role

Catheter ablation therapy involves ‘burning’ small areas of cardiac tissue in order to permanently disrupt the problematic electrical pathways driving potentially lethal arrhythmias. However, procedure times and complication rates are high, whilst success rates are punitively low (~50% success), largely due to the significant challenges clinicians face in identifying the ideal ‘target’ to ablate. Here, we aim to further develop, and clinically validate, a novel in-silico tool that uses patient imaging data to reconstruct personalised ‘digital twin’ cardiac models to provide pre-procedural ablation target guidance. This will provide essential confidence and data to guide a follow-up prospective randomised clinical trial.

In this project, funded by an internal MRC Impact Acceleration Award, we will use currently-collected patient imaging data to further develop computational pipelines to reconstruct personalised image-based computer models of a patient’s heart. Imaging data, from modalities such as Cardiac MRI and Cardiac CT will be combined in order to best represent the patient’s cardiac anatomy, as well as the underlying fibrosis and scar tissue which are responsible for driving the lethal ventricular arrhythmias to be treated.  These patient models will then be used within our novel in-silico approach (patent filed) to rapidly simulate patient arrhythmias in near-real time. A crucial aspect of this work will be the further adaptation of this computational approach in order to automatically account for the inherent uncertainty in the clinical data, for example by considering different representations of the scar or of the functional parameters that go into the model. Finally, clinical electrical data from the cath-lab during patient procedures, in the form of both ECG and invasive electro-anatomical mapping data, will then be used to validate the arrhythmia ‘circuits’ predicted by the model.

This is a full time post (35 Hours per week), and you will be offered a fixed term contract up to 1 year.

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

1st or 2nd class hons degree in computer science, biomedical engineering, physics, mathematics or related subject  

PhD qualified in computer science, biomedical engineering, physics, mathematics or related subject (or pending results)* 

Good programming skills in Python, Matlab and/or C++ 

Experience in computational biophysical modelling and simulation 

Good writing and presentation skills 

Desire to work in medical modelling in a clinical environment 

Flexible approach to hours of work and duties 

Able to work on own initiative and in a team, and communicate effectively with people from wide variety of disciplines and organisations

* 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.

Desirable criteria

Knowledge of cardiac physiology 

Knowledge of how to perform numerical simulations and analysis 

Advanced knowledge of signal and image processing techniques 

Experience in cardiac research

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

Further information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.

We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

To find out how our managers will review your application, please take a look at our ‘How we Recruit ’ pages.

We are able to offer sponsorship for candidates who do not currently possess the right to work in the UK.

Requirements
Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

KINGS COLLEGE LONDON

Country

United Kingdom

City

London (Central)

Geofield

Where to apply

Website

https://www.timeshighereducation.com/unijobs/listing/372434/research-associate-…

Contact

City

London (Central)

STATUS: EXPIRED