Postdoctoral Research Associate in Machine Learning for Cardiovascular Digital Twins

Queen Mary University of London; Greater London; On-site; GBP 34,000 - 42,000; Full time

Benefits offered by this job

30 days leave per year (pro-rata)

Pension scheme

Season ticket loan

Personal and professional development

Flexible working

Job summary

Queen Mary University of London seeks a Postdoctoral Research Associate in Machine Learning for Cardiovascular Digital Twins. The role focuses on developing patient-specific models integrating multimodal clinical, physiological, imaging and sensor data to predict disease state and treatment response.

Based in DERI and CVDHub, you will contribute to AI-enabled precision treatment and publish high-quality research.

Qualifications

• PhD in computer science, engineering, mathematics, or similar.
• Strong programming skills and experience with a contemporary ML framework such as PyTorch.
• Knowledge of software development principles and ML including deep learning.

Responsibilities

• Develop patient-specific models integrating multimodal data to predict disease state and treatment response.
• Research in ML for cardiovascular digital twins and AI-enabled precision treatment.

Skills

Machine Learning

Python

PyTorch

Research

Education

PhD in CS/Engineering/Mathematics

Tools

PyTorch

Job description

About the Role

We are seeking a Postdoctoral Research Associate in Machine Learning for Cardiovascular Digital Twins to join a team working on the Precision Health, Cardiovascular Devices and Trials Theme, of the NIHR Biomedical Research Centre Award. Funded by the National Institute for Health and Care Research Barts Biomedical Research Centre, the role will focus on undertaking research in machine learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data to predict disease state, treatment response and the likely consequences of alternative clinical interventions.

The position is funded until March 31st 2028 in the first instance, and available immediately.

About You

You will have a PhD in computer science, engineering, mathematics, or similar, strong programming skills, and experience with a contemporary machine-learning framework such as PyTorch. You will have knowledge of software development principles, and machine learning, including deep learning experience, as well as a strong background in research processes, including report writing, and producing high-quality publications.

About the School/Department/Institute/Project

You will be based in the Digital Environment Research Institute (DERI) and the Cardiovascular Devices Hub (CVDHub). DERI is Queen Mary’s first University Research Institute dedicated to ground-breaking multi-disciplinary research in digital and data science, including artificial intelligence (AI). The role is jointly split with the Cardiovascular Devices Hub which brings together clinicians, academics, engineers and industry to develop innovative solutions to unmet clinical needs.

About Queen Mary

At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the previously unthinkable. Throughout our history, we’ve fostered social justice and improved lives through academic excellence. And we continue to live and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers. We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.

Benefits

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. 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.