Applications are invited for a Postdoctoral Research Associate with experience in machine and deep learning to work on a research project funded by the Precision Health, Cardiovascular Devices and Trials Theme, part of a recent NIHR Biomedical Research Centre Award to Barts Health NHS Trust.
The research will involve using the cardiovascular digital twin concept to digitally model three disease states: acute coronary syndromes, valvular heart disease and hypertension. These models will be created by inputting data from available existing and novel wearables, sensing technologies, apps and large data registries. Using this data, digital models will be created to provide personalised patient treatment plans supporting their disease management, predicting disease states/trends and enabling device choice/design by predicting the patient’s response.
The role is funded for 3 years in the first instance.
The ideal candidate will have a PhD in a numerate field with expertise in machine and deep learning methods, supported by high quality publications. Experience applying such methods to healthcare data is an advantage.
Appointments at grade 4 through to grade 5 and offers will be made based on level of experience in relation to the duties and expectations of the role and person specification, as outlined in the Job Profile.
We offer competitive salaries, access to a generous pension scheme, 30 days’ leave per annum (pro-rata for part-time/fixed-term), a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and campus facilities including an on-site nursery at the Mile End campus.
Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.
Valuing Diversity & Committed to Equality