Research Assistant in Data Science

About the Role
Pregnant women have historically been under-represented in drug safety research, leaving prescribers and patients to weigh treatment decisions with limited evidence. This new post contributes to a programme aimed at changing that. It sits at the forefront of medical research, combining epidemiology, medical statistics, data science, and clinical medicine to address important public health challenges. Using large and complex electronic healthcare records, the postholder will support high-impact research with a primary focus on medication safety, children’s, women’s and public health.

The postholder will work principally on an ambitious, recently funded programme establishing the safety profile of medicines in pregnancy, with particular attention to longer-term outcomes in offspring. They will undertake original research through complex analyses of anonymised clinical research databases, applying advanced statistical and artificial intelligence methods.

About You
This role is ideally suited to a proactive and ambitious researcher with an MSc in health data science, clinical epidemiology, or medical statistics, who is planning or has begun an academic career in this area.

You will have experience analysing large and complex datasets, strong programming skills in Stata, R or a comparable environment, and the ability to work independently under general supervision. You will be expected to contribute to peer-reviewed publications, present at conferences, and uphold rigorous standards of information governance and collaborative working.

Experience with electronic healthcare records (such as the QResearch Database), Trusted Research Environments, and artificial intelligence or machine learning methods would be advantageous.

About the School/Department/Institute/Project
The postholder will join the Primary Care Epidemiology Unit, within the Centre for Primary Care. The group, recently relocated to Queen Mary University of London (QMUL), comprises academics, researchers, clinicians, data scientists, and software engineers. It specialises in advanced analyses of large electronic healthcare record databases such as QResearch, generating new knowledge to improve patient care across a wide range of clinical conditions. Current work includes evaluating the risks and benefits of commonly prescribed medications, and developing, validating, and implementing prediction algorithms as clinical tools within the NHS.

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.

Advert information