Professor In Global Health Data Science

• Blantyre, Malawi
• Contract (Full-Time)
• Closing Date: 20/05/2026

The Malawi-Liverpool-Wellcome Programme (MLW) stands as a world-class health research institution, dedicated to enhancing health outcomes through cutting-edge research, robust capacity building, and strategic collaborations.

MLW is currently seeking an accomplished data scientist to establish and lead a new team of data scientists within its recently established Data Science and Computational Modelling Unit (DSCMU).

This role is a collaborative initiative involving MLW's DSCMU and the Civic Health Innovation Labs (CHIL) at the University of Liverpool. The successful candidate will be affiliated with CHIL and the Department of Health Data Science, both housed within the University’s Institute of Population Health. CHIL operates as an interdisciplinary research centre, with the University of Liverpool acting as a key strategic partner for MLW.

This position is situated at MLW's head offices in Blantyre.

POSITION FUNCTION (PURPOSE)

The chosen candidate is expected to spearhead and deliver world-leading research in the field of health data science. In addition to their reputation as a respected expert in their discipline, the individual must be capable of:

• Establishing and leading a team of data scientists at MLW.
• Providing strategic leadership within their specialty, demonstrated by a robust record of interdisciplinary, team-based scientific achievements, including publications in peer-reviewed journals.
• Exhibiting a strong history of securing external funding from a variety of sources.
• Identifying and pursuing new strategic interdisciplinary research opportunities, alongside diversifying funding streams to ensure sustained success.
• Demonstrating exceptional proficiency in communicating research findings to key stakeholders, including decision-makers, media, and the public.
• Strengthening and expanding partnerships in this domain across the region and globally.
• Championing data science initiatives to MLW, as well as to national, regional, and international collaborators.
• Designing and delivering effective teaching and training resources for both staff and students.

Applicants must hold a PhD (or an equivalent qualification) in a relevant health data science field. As an academic staff member, the successful candidate will be required to contribute to teaching activities.

Those without a formal teaching qualification will need to acquire one through the University.

Additional information regarding this vacancy, the application procedure, and the full job description is available. Applications must be submitted no later than 20th May 2026.