Mathematical modelling and data integration to derive correlates of protection against invasive non-typhoidal Salmonella (iNTS) disease in African children

Invasive non-typhoidal Salmonella (iNTS) disease is a leading cause of bloodstream infection and death in young children across sub-Saharan Africa, and the World Health Organization (WHO) ranks an iNTS vaccine among its top-ten vaccine priorities for the continent. A critical gap identified in the WHO iNTS vaccine R&D Roadmap is the absence of a validated correlate of protection (CoP); a measurable immune marker that predicts who is protected against invasive disease. Without a CoP, the development, licensure and deployment of candidate iNTS vaccines is slow and costly.

The Protection Against iNTS (PAINTS) project is an international, multidisciplinary vaccinology consortium funded by the Wellcome Trust and led by the University of Edinburgh, established to derive an evidence-based, functionally validated and internationally standardised CoP for iNTS disease. The consortium includes 5 UK academic partners as well as 3 LMIC partners in Malawi and DR Congo, and an industrial global health partner (GSK Vaccines for Global Health). The Work Package in which this studentship is embedded characterises endemic paediatric populations with natural exposure to NTS at two African field sites; in Malawi (Malawi-Liverpool-Wellcome Programme) and the Democratic Republic of Congo (Institut National pour la Recherche Biomedicale), linking age-stratified serological immunity to detailed epidemiological metadata.

This project is focused on the mathematical modelling, statistical analysis and integration of data generated across both field sites. The central premise is that invasive disease declines after the first year of life despite continued enteric exposure, implying that protection is driven by naturally acquired O-antigen IgG, rather than by waning exposure. By jointly modelling age-stratified antibody titres, the force of enteric exposure (faecal NTS carriage) and the established age-specific incidence of invasive disease, the protective effect of antibody can be separated from changing exposure and a putative antibody threshold of protection derived.

The successful candidate will build and fit these models, integrate immunological and epidemiological datasets from Malawi and DRC, and quantify how risk factors such as malaria, anaemia and malnutrition modify the immune response and the protective threshold across settings. This work will define the “protective immunity gap” that a vaccine must fill in different epidemiological contexts and generate policy-relevant evidence to accelerate iNTS vaccine licensure and deployment. The exact objectives will be refined jointly by the student and the supervisory team, but may include:

• Integrating and harmonising serological and epidemiological datasets across the Malawi and DRC field sites.
• Developing and fitting mathematical and statistical models to age-stratified data on O-antigen IgG, enteric NTS infection and invasive disease incidence to derive putative protective thresholds.
• Exploring and quantifying the effect of force of infection and host risk factors (malaria, anaemia, malnutrition, sickle cell disease) on acquired immunity and the protective threshold across both sites
• Comparing exposure and the acquisition of immunity between sites to characterise how the protective immunity gap varies geographically.
• Validating the candidate correlate against additional serological or functional measures generated by consortium partners.
• Contributing to reports, publications and consortium outputs 

This position brings the opportunity to work in an area of high global health priority and impact, as part of a large Wellcome-funded international consortium. It is possible that the candidate may have opportunity to travel for national and/or international collaborations within the PAiNTS consortium.

Supervisors

• Professor Melita Gordon; AXA Research Professor in Vaccinology and Global Health, Chief Investigator of the PAiNTS Consortium, Centre for Global Health, Usher Institute, The University of Edinburgh. 
• Professor Katie Atkins; School of Population Health Sciences, Usher Institute, The University of Edinburgh.

In collaboration with:

• Malawi-Liverpool-Wellcome Trust Programme (MLW) and Kamuzu University of Health Sciences (KUHeS), Malawi 
• Institut National de Recherche Biomédicale (INRB) and partners, Kinshasa, Democratic Republic of Congo.
• Wider PAINTS consortium partners across immunology, serology and vaccinology.

Requirements

A strong academic track record with a 2:1 or higher in a relevant undergraduate degree, or its equivalent if outside the UK. 

A Masters degree in a relevant quantitative discipline (e.g. epidemiology, biostatistics, mathematical modelling, infectious disease epidemiology, immunology with a quantitative focus, or a related field) is desirable. 

Proven experience in one or more of the following is desirable: mathematical or statistical modelling of infectious diseases, data integration and curation of complex datasets, and scientific programming in at least one language (e.g. R, Stata, Python). 

An interest and experience in infectious disease immunology, vaccinology or serology, and experience working with field epidemiological data. 

The successful candidate will work in a highly interdisciplinary, internationally distributed consortium and should be able to work both independently and as part of a team. A commitment to or experience in Global Health would be advantageous

Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Population Health Sciences PhD programme. Details about the PhD programme can be found here: http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=213

Application procedure

Please provide a CV, a personal statement detailing your research interests and reasons for applying, degree certificate(s), marks for your degree(s) and 2 written academic references. All applications documents should be in electronic format and sent via e-mail to Marianne Chiu-Lezeau (mchiule@ed.ac.uk) (You do not need to submit an application via the University application portal at this stage.)

Informal enquiries are encouraged to Melita Gordon (mgordon5@ed.ac.uk)

The closing date for applications is 30 July 2026

Interviews will be held during August / Sept 2026

The position will commence in Sept / Oct 2026