Call for two PhD Positions under the Global Health EDCTP3 Joint Undertaking funded Digital Dashboards in Diagnostic Innovations (DiDiDi) Project

Leiden University Medical Center (LUMC), The Netherlands, The University of Glasgow, Scotland, UK, Makerere University (Mak), College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB) and College of Computing and Information Science Kampala,  Uganda.

Makerere University (Mak) in collaboration with The Leiden University Medical Center (LUMC) and The University of Glasgow, Scotland, UK invites applications for two PhD positions.  The PhD position is under our four (4) year (2026-2030) funded project by Global Health EDCTP3 Joint Undertaking and implemented through EU Funding & Tenders Portal under project name: Digital Dashboards in Diagnostic Innovations (DiDiDi) involving 16 research partner institutions from 6 countries, including LUMC, The University of Glasgow and Makerere University.

Project background

Digital Dashboards in Diagnostic Innovations (DiDiDi)  focuses on developing secure digital dashboards to understand disease prevalence and to target new interventions for the treatment of these poverty related helminth infections. Schistosomiasis and soil‑transmitted helminth infections remain major public health challenges in Uganda and other endemic regions. Accurate and scalable diagnostic tools are essential for targeted treatment, monitoring of control programs, and progress towards elimination. The project has a specific focus on government and regional health surveillance systems, meteorological data collection and predictive models.

PhD Positions

PhD Position 1: Field-evaluation of diagnostic innovations for schistosomiasis and Soil‑Transmitted Helminth infections in Uganda

Within the DiDiDi consortium, this PhD project specifically contributes high‑quality field and clinical validation data to support the development and evaluation of digital diagnostic dashboards. The goal for the PhD is to collect and analyse clinical and field data in Uganda and to validate conventional diagnostic approaches against innovative digital diagnostics and environmental risk factors. The work will contribute to a better understanding of infection dynamics and to the development of improved diagnostic and surveillance strategies in endemic settings in low‑ and middle‑income countries (LMICs) to conduct doctoral research on the diagnosis of schistosomiasis and soil‑transmitted helminth (STH) infections in endemic settings.

PhD Position 2: Developing Machine Learning for Microscope Decision Support for Schistosomiasis and Soil‑Transmitted Helminth infections in Uganda

Within the DiDiDi consortium, this PhD project specifically contributes high‑quality field and clinical validation data to support the development and evaluation of digital diagnostic dashboards. As part of this programme, we are further developing low-cost automated microscopy that can be readily deployed in community settings. The goal for the PhD is to develop computationally low-resource mobile phone-based machine learning and AI algorithms to analyse field data. The work will involve the opportunity to collaborate with industrial partnerships based in Uganda and Europe. The overall aim of the project will be to contribute to a better understanding of infection dynamics and the development of improved diagnostic and surveillance strategies in endemic settings in low‑ and middle‑income countries (LMICs).

Application Process

Interested candidates should submit:

• A motivation letter describing research interests and suitability for the project;
• Curriculum vitae.
• Only apply for one PhD track

Following a first selection round, potential candidates will be asked for:

• Copies of academic transcripts and degree certificates;
• Names and contact details of at least two academic referees.

A first round of interviews is likely to take place in Kampala on May 17^th or 18^th.

Submission Process

Submit your application to the project contact person at Makerere University, Associate Professor Lawrence Mugisha via email: mugishalaw@gmail.com not later than 7^th May, 2026. For PhD 1, copy in E.A.van_Lieshout@lumc.nl while for PhD 2 copy in jon.cooper@glasgow.ac.uk

Only shortlisted candidates will be notified for the 1^st phase of the interview.

See below for detailed advert