Research Associate in AI for Healthcare Data Science
Apply advanced AI and machine learning to transform healthcare data for improved patient outcomes and reduced inequalities.
Best for:Best for AI/ML researchers with expertise in healthcare data, strong Python/R programming skills, and a passion for translating data science into real-world healthcare improvements.
Overview
The University of Liverpool invites a Research Associate to join the Civic Health Innovation Labs (CHIL), a leading research centre focused on leveraging artificial intelligence and advanced analytics to enhance healthcare services. Based in the Faculty of Health and Life Sciences, this role involves developing cutting-edge AI solutions, analysing complex health datasets, and collaborating with academic, NHS, industry, and policy partners. The successful candidate will contribute to knowledge exchange, research dissemination, and shaping the future of data-driven healthcare innovation. This position is fixed-term until March 31, 2031, offering a dynamic environment for impactful research in healthcare AI.
What you'll do
- Develop and deliver advanced AI and machine learning solutions to analyse complex health and population datasets.
- Build secure, reproducible AI pipelines for healthcare data processing and analysis.
- Collaborate with academic, NHS, industry, policy, and public partners to generate actionable insights for healthcare improvement.
- Contribute to knowledge exchange, capacity building, and research dissemination through publications, presentations, and funding applications.
- Shape the future of data science and AI within an interdisciplinary research environment focused on reducing health inequalities.
- Work closely with the HealthTech Design Studio to translate research into practical healthcare applications.
Requirements
Degree required: PhD (or equivalent professional experience) in data science, computer science, statistics, or a related quantitative discipline
Language: English; proficiency at a level suitable for academic research and collaboration
Instruction: English
- Proven expertise in machine learning and AI techniques
- Strong programming skills in Python or R
- Experience working with large and complex healthcare datasets
- Ability to communicate technical findings to both technical and non-technical stakeholders
- Experience with secure and reproducible data analysis pipelines
- Applicants awaiting PhD confirmation may apply at a lower grade (Grade 6) with a salary increase to Grade 7 upon PhD award confirmation
- No explicit nationality or residency restrictions mentioned
Funding & terms
How to apply
Deadline: 2026-10-20 (Europe/London)
Applicants must submit their CV and a cover letter outlining their relevant experience and how it aligns with the role through the university's online recruitment portal. Additional documents may be requested during the application process.
- CV
- Cover letter
- Proof of PhD status (if applicable)
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