PhD in Biomedical Engineering - AI Enabled Low Cost Microscopy for Neglected Tropical Diseases in East Africa
About the Project
Applications are invited for a 42-month fully funded PhD focused on developing low-cost, AI-enabled microscopy for detecting neglected tropical diseases in East Africa. Based in the Advanced Research Centre at the University of Glasgow, the successful candidate will design and validate ultra-low-cost optical systems and machine-learning algorithms for automated diagnosis in community settings. Close collaboration with Zeiss Microscopy in Jena, Germany will provide training in advanced imaging and optical engineering.
The primary targets are schistosomiasis and soil-transmitted helminths (STH), which remain widespread in under-served rural communities where access to reliable diagnostics is limited. Delays in detection contribute to avoidable morbidity, and with an estimated 240 million people affected by schistosomiasis in Africa, there is an urgent need for affordable, field-ready tools to support community health workers and strengthen disease-control programmes.
Beyond diagnostic innovation, the project will explore how disease prevalence relates to meteorological determinants such as precipitation and temperature, and how climate-driven patterns of infection can inform the deployment of healthcare resources. This studentship offers a unique opportunity to contribute to an international partnership integrating AI, global health, environmental data science and climate-health research. It is ideally suited to highly motivated candidates with strong backgrounds in physics, optics or biomedical engineering who are committed to developing impactful technologies for global health equity.
This PhD forms part of a wider EDCTP-funded initiative under the DIDIDI programme involving European and African partners working to improve health through research and innovation. You will collaborate with the Ministries of Health in Uganda and Kenya and undertake field studies to ensure real-world relevance and operational readiness of the low-cost microscopy systems.
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