Supervisors: Prof Melita Gordon, Prof Katie Atkins
Funding: Funded PhD Project (Students Worldwide)
About the Project
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 Biomédicale), linking age-stratified serological immunity to detailed epidemiological metadata.
The project is centred on mathematical modelling, statistical analysis and integration of data generated across both field sites, and is best suited to a candidate with a relevant degree with strong quantitative components who wants to apply those skills to a high-impact global health problem. No wet-lab or field work is involved.
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:
- Developing and fitting mathematical and statistical models (e.g. mechanistic/compartmental, survival, or Bayesian hierarchical frameworks) to age-stratified data on O-antigen IgG, enteric NTS infection and invasive disease incidence to derive putative protective thresholds.
- Integrating and harmonising serological and epidemiological datasets across the Malawi and DRC field sites, including building reproducible data pipelines for complex, real-world data.
- 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, using appropriate statistical inference methods.
- Comparing exposure and the acquisition of immunity between sites to characterise how the protective immunity gap varies geographically.
- Statistically 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 the 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
Essential
- A strong academic track record, with a 2:1 or higher (or international equivalent) in a relevant undergraduate degree with strong quantitative components.
- 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).
- Skills and proven experience in data integration and curation of complex datasets, and scientific programming in at least one language (e.g. R, Stata, Python).
- Proven experience in in mathematical modelling, particularly mathematical modelling of infectious diseases.
Desirable
- An interest and experience in infectious disease immunology, vaccinology or serology.
- 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, translating quantitative findings for an audience of immunologists, clinicians and field epidemiologists. 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; including your quantitative background and any modelling experience, degree certificate(s), marks for your degree(s), and 2 written academic references. All application 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).
- Closing date for applications: 26 October 2026
- Interviews: November 2026
- Position commences: January 2027
Funding Notes
This position is funded internally by Edinburgh University, as part of the matched funding/contribution pledge for Prof Melita Gordon’s AXA Research Fellowship, at UK/Home rate. It is a computational studentship using existing datasets, with no wet-lab or field-work costs. The candidate will require a laptop and possibly additional analysis or modelling software.
- Full fees (Home/UK and international rate) covered by UoE PhD Tuition Fee Contribution Scheme for 3 years
- Stipend at UKRI rate (£21,805 p.a. in 26/27) for 3 years
- Additional Programme Costs £5,000 per annum for 3 years
- Conference travel of up to £300 p.a. for 3 years