Research Associate in AI for Health Data Systems

Location: White City Campus (Hybrid)

About the role:

Do you want to shape how artificial intelligence is applied to real-world health challenges in low- and middle-income countries? We are seeking a Research Associate in AI for Health Data Systems to join a Gates Foundation-funded collaboration to strengthen Ethiopia's health data ecosystem. You will design and implement AI/ML methodologies and lead capacity-building activities with Ethiopian partners to deliver practical impact on national health priorities such as vaccine uptake and child health.

What you would be doing:

• Lead AI-driven data analysis and modelling workflows for public health decision-making.
• Build secure, reproducible AI/ML pipelines using modern tools and large language models.
• Co-design, deliver and evaluate priority use cases with Ethiopian peers, ensuring knowledge transfer.
• Mentor and train local practitioners in applied AI/ML techniques tailored to the Ethiopian context.
• Translate technical outputs into accessible dashboards, reports and policy briefs for stakeholders.
• Contribute to manuscripts, internal reporting and competitive grant/fellowship bids.

What we are looking for:

• PhD (or near completion) in Computer Science, Data Science, Epidemiology or a related field with a strong AI/ML component.

• Proven hands-on application of AI/ML to real-world datasets (ideally health/public sector).

• Strong programming skills (e.g. Python; PyTorch, JAX, HuggingFace). Excellent communication and collaboration with diverse stakeholders (academia, policy makers).

• Evidence of mentoring/training and community building.

• Experience working internationally, ideally in LMIC and ideally sub-Saharan Africa

• Experience working with secure data connectors (e.g. MCP), modern LLMs/agentic tooling.

• Background in global health/epidemiology.

• Interest in gender equity and bias mitigation in AI.

What we can offer you:

• A major international project with real-world impact in global health.
• Mentoring from leading scientists plus hands-on training in AI, modern statistics and health data science.
• Collaboration through the Machine Learning & Global Health Network (MLGH).
• Opportunities to publish in high-quality journals and present at leading conferences.
• Development of teaching, supervision and grant-writing skills.
• 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.
• Sector-leading salary and remuneration package (including 41 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

This is a full-time post based at Imperial College London's White City Campus.

This role is for a fixed-term contract until 30 June 2027.

If you require any further details about the role, please contact: Dr Elizaveta Semenova - e.semenova@imperial.ac.uk.

£49,017 to £57,472 per annum

• PhD (or near completion) in Computer Science, Data Science, Epidemiology or a related field with a strong AI/ML component.

• Proven hands-on application of AI/ML to real-world datasets (ideally health/public sector).

• Strong programming skills (e.g. Python; PyTorch, JAX, HuggingFace). Excellent communication and collaboration with diverse stakeholders (academia, policy makers).

• Evidence of mentoring/training and community building.

• Experience working internationally, ideally in LMIC and ideally sub-Saharan Africa

• Experience working with secure data connectors (e.g. MCP), modern LLMs/agentic tooling.

• Background in global health/epidemiology.

• Interest in gender equity and bias mitigation in AI.

What we can offer you: * A major international project with real-world impact in global health. * Mentoring from leading scientists plus hands-on training in AI, modern statistics and health data science. * Collaboration through the Machine Learning & Global Health Network (MLGH). * Opportunities to publish in high-quality journals and present at leading conferences. * Development of teaching, supervision and grant-writing skills. * 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. * Sector-leading salary and remuneration package (including 41 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.