Research Assistant in AI

Queen Mary University of London
London
Today
£39,187 – £39,802 pa

Salary

£39,187 – £39,802 pa

Job Type
Contract
Work Pattern
Full-time
Seniority
Entry
Education
Masters
Posted
10 Nov 2026 (Today)

Benefits

Generous pension scheme 30 days' leave per annum (pro-rata for part-time/fixed-term) Season ticket loan scheme Personal and professional development opportunities Work life balance and family friendly, inclusive employment policies Flexible working arrangements Campus facilities

About the Role
Applications are invited for a Research Assistant in AI at the Centre for Clinical Pharmacology and Precision Medicine, William Harvey Research Institute. You will support NIHR Barts Biomedical Research Centre projects applying computational and AI approaches to cardiovascular research. Working within a multidisciplinary team, you will prepare and manage large-scale clinical, imaging and linked healthcare datasets, develop reproducible data-processing pipelines, and develop and validate AI-based cardiovascular risk prediction models. Research will focus on cardiomyopathies, hypertension and inherited arrhythmias, assessing model performance, generalisability and clinical applicability in real-world datasets.

About You
You will have an undergraduate degree in a relevant quantitative field, such as computing, mathematics, bioinformatics or statistics, together with a relevant postgraduate degree such as an MSc. You will have experience of undertaking a research or data-analysis project and strong computational, statistical and analytical skills. Experience of Python programming, basic shell scripting, and developing software, data-processing pipelines or predictive models is essential. You will be highly organised and accurate, with strong written and verbal communication skills. Self-motivated and enthusiastic about research, you will be comfortable working collaboratively within a multidisciplinary team of clinicians, geneticists, data scientists and other researchers.

About the School/Department/Institute/Project
The William Harvey Institute is a world-leading centre for research, with a vibrant, multidisciplinary scientific environment devoted to therapeutic innovation in cardiovascular, endocrine and inflammatory.

A number of large-scale patient and cohort studies are taking place to address genetic, demographic and lifestyle risk factors associated with the cardiovascular system and develop new tools for improved disease diagnosis, prediction, and treatment. The Barts BRC at QMUL and Barts Health Trust will support and coordinate projects aiming to address challenges in CVD research and work in concert with partners at the British Heart Foundation (BHF)-NIHR Cardiovascular Partnership as well as the BHF Accelerator internally.

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.

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