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Kath O'Reilly

Associate Professor, co-Director Mathematical Modelling (CMMID)

London School of Hygiene & Tropical Medicine

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United Kingdom

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Research Interests

Epidemiology

10%

Statistics

10%

Mathematics

10%

Salud Pública

10%

Mathematical Modeling

10%

Disease Surveillance

10%

Data Science

10%

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Positions1

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Kath O'Reilly

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London School of Hygiene and Tropical Medicine, University of London

PhD in Infectious Disease Epidemiology and Mathematical Modelling at LSHTM

The London School of Hygiene and Tropical Medicine (LSHTM) is offering a PhD opportunity in Infectious Disease Epidemiology and Mathematical Modelling, supervised by Associate Professor Kath O'Reilly and Marc Bauguellin. The successful applicant will join the modelling HPRU at LSHTM, working across disease specialisms and collaborating with teams in CMMID, HPRU, and LSHTM. Research topics include the development and evaluation of disease surveillance systems for early detection of pandemics, with a particular focus on innovative approaches such as wastewater surveillance. These questions are highly policy-relevant and remain largely unanswered, offering a unique chance to contribute to global health preparedness. Applicants should have a strong background in mathematical modelling, epidemiology, or statistics, and those currently studying for a MSc in related fields are especially encouraged to apply. The position is open only to students eligible for UK home fees. Funding information is available through the LSHTM research degree funding and scholarships page, and applicants are encouraged to review these details to determine their eligibility and potential support. The application deadline is in late March 2026. Interested candidates should review the full details and funding options at the LSHTM website and prepare their application materials accordingly. This is an excellent opportunity for students passionate about public health, data science, and infectious disease research to join a leading institution and contribute to impactful, policy-driven research.

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