About this role
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 – [email protected].