Research Assistant in Data Health Science

Imperial Enterprise; Gloucester; On-site; GBP 36,000 - 50,000; Full time

Job summary

Imperial College London invites applications for a Research Assistant in Data Health Science based in the Health Impact Lab. You will work with large linked health records to model lipid risk and cardiovascular prevention strategies.

The role focuses on building reproducible analyses inside secure NHS-linked environments, developing risk stratification tools, and informing NHS partners on pathways to improve lipid management across London.

Qualifications

• Hands-on experience analysing large-scale routinely collected healthcare data – linked primary and secondary care records, national claims data or hospital data warehouses – and 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.

Responsibilities

• Review literature on lipid management, patient profiling and treatment gaps to frame the data questions.
• Build and validate a reproducible analytical pipeline inside the London Secure Data Environment, using linked primary and secondary care records.
• Develop and evaluate models of cardiovascular outcome risk and health economic models.
• Co-design novel lipid risk identification and management pathways with NHS partners for prospective validation.
• Publish findings, present to academic and NHS audiences, and supervise undergraduate and master's students.

Skills

SQL

Python

Education

Bachelor's degree in medicine or health/science

Master's in medical informatics / health data science / public health / epidemiology

Job description

Research Assistant in Data Health Science

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 – [e-mail]

Attached documents are available under links. Clicking a document link will initialize its download.

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

We reserve the right to close the advert before the stated closing date, should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.

If you encounter any technical issues while applying online, please don't hesitate to email us at [e-mail]. We're here to help.

About Imperial

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