Research Assistant in Data Health Science

Job description

About the role

Can you work with ten million patient records to create a better way of preventing heart attacks and strokes? We are looking for a Research Assistant in Health Data Science, focussing on lipid risk and cardiovascular prevention, to join the Health Impact Lab at Imperial College London. Working inside the London Secure Data Environment to find the people whose cardiovascular risk is not being controlled - and to work out, patient by patient, how to solve this.

Raised LDL cholesterol is one of the few causes of cardiovascular disease that is both cheap and straightforward to treat. Yet in every health system that has looked, most high-risk patients never reach the recommended target. Some are undertreated, some are not taking the treatment they have been prescribed, and some simply do not respond to it. Those three problems need three different answers, and routine NHS data can tell them apart.

This is a 12-month post in the first instance, with scope to extend. It runs from a review of the evidence, through model building and validation, to the design of new lipid management pathways ready for prospective clinical validation with NHS partners.

What you would be doing

You will review the clinical, methodological and health economic literature on lipid management, patient profiling and treatment gaps, and use it to frame the questions the data can answer.

You will build and validate a reproducible analytical pipeline inside the London Secure Data Environment, working with linked primary and secondary care records for an unselected London-wide population. That means curating coded clinical, prescribing and pathology data, reconstructing treatment exposure over time, stratifying cardiovascular risk against guideline criteria, and separating undertreatment, non-adherence and non-response as distinct and actionable phenotypes.

You will develop and evaluate models of cardiovascular outcome risk, and health economic models that put a cost, a quality-adjusted life year and an inequality consequence against each alternative pathway design - so that a commissioner can see what a programme would cost, what it would prevent, and who it would reach.

You will then take that work out of the analytical environment. Alongside clinical and analytical teams in the Integrated Care Board, general practices, primary care networks and community pharmacy, you will co-design novel pathways for lipid risk identification and management and prepare them for collaborative prospective clinical validation - including protocol development, ethics and data protection approvals, and site engagement.

You will publish your findings, present them to academic and NHS audiences, and help supervise undergraduate and master's students.

What we are looking for

Full essential and desirable criteria are set out in the job description. In summary, we are looking for:

• A first degree in medicine, or in a health, life or quantitative science, together with a master's level qualification in medical informatics, health data science, public health or epidemiology.
• Hands-on experience analysing large-scale routinely collected healthcare data - linked primary and secondary care records, national claims data or hospital data warehouses - and of working inside a secure data environment under information governance and output-checking rules.
• Fluency in SQL and Python for cohort definition, phenotyping and model development, with sound judgement about evaluation: what a model is being asked to do, and what performance would mean clinically.
• Experience of prospectively evaluating a decision support tool or digital health intervention with clinician participants, and a record of peer-reviewed publication.
• Knowledge of cardiovascular risk stratification and lipid management, including ESC/EAS and NICE guidance on LDL cholesterol targets and lipid-lowering therapy.
• The ability to move in both directions between a clinical question and an analysable specification - and to explain the result to a general practitioner, a commissioner or a statistician, as the situation requires.

What we can offer you

In addition to the generic benefits below, this post offers:

• A programme of work with a clear line from analysis to patient benefit: the modelling you do is intended to change how lipid risk is identified and managed across a population of around three million people.
• Access to the London Secure Data Environment and to one of the richest linked primary and secondary care datasets in the world.
• Direct working relationships with NHS Integrated Care Board clinical and analytical teams, general practice and community pharmacy - the people who would run the pathway you design.
• Supervision from practising clinician-academics in a lab whose work appears in highest impact outlets, and support to complete a doctorate alongside the post.
• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: gain access to Imperial's sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• As a member of research staff, you have 10 development days to use to develop your skills and explore your career prospects
• Sector-leading salary and remuneration package (including 43 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

The post is full-time fixed term for a duration of 12 months and is expected to start no later than 1 November 2026. The post is based at the White City Campus, with the possibility of extension.

If you require any further details about the role, please contact: Professor Nicholas S Peters - [email protected]