Research Fellow (Infectious Disease Modelling), Singapore

Job Description
Job Description
We are seeking a Research Fellow to join a new group within the Centre for Epidemic Research and Modelling (CERM) at Saw Swee Hock School of Public Health at the National University of Singapore (NUS) led by Professor Azra Ghani.
You will lead research in the development and application of within-host mathematical models to understand the long-term dynamics of natural- and vaccine-induced immunity to pathogens. You will be responsible for developing a suite of within-host mathematical models of that can be used to test hypotheses regarding the durability of acquired immunity through natural infection, vaccination or in combination (i.e. hybrid immunity).
This new project forms part of a wider multi-country collaborative initiative that is seeking to develop novel, high-throughput immunological assays to improve surveillance of spillover of viral families of pandemic potential. This includes teams from Singapore (NUS, Duke-NUS, EBI/A*Star), Vietnam (Oxford University Clinical Research Unit, National Institute of Hygiene & Epidemiology), Cambodia (Institut Pasteur) and the UK (University of Oxford & Imperial College London).
You will work closely with the modelling team in this initiative at NUS (directed by Dr Hannah Clapham) and at Imperial College London / Imperial Global Singapore (directed by Professor Azra Ghani).
Alongside the project-specific team, the postholder will benefit from joining a vibrant, established team of mathematical modellers and epidemiologists at CERM with strong collaborative links within Singapore and across the wider region.
Key Responsibilities
Collate and analyse data from longitudinal studies following immune dynamics in response to infection and/or vaccination Develop within-host mathematical models of the immune response to pathogens Collaborate with the wider interdisciplinary team of researchers, including virologists, immunologists and bioinformaticians Disseminate research findings through peer-review publications and presentation at international meetings and conferences Assist in the supervision and mentoring of graduate students and junior researchers Contribute to future grant proposal developments
Application Process
Interested applicants should submit the following documents:
A cover letter explaining your interest in the position, relevant experience, and research interests. A detailed CV, including a full list of publications. Contact information for three professional references who can provide letters of recommendation upon request.
Review of applications will begin immediately and continue until the position is filled. The anticipated start date is 1st October 2025 onwards. The initial appointment will be for 1 year with renewal up to 2 years depending on satisfactory performance.
NUS is an equal-opportunity employer committed to diversity and inclusion. We welcome applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, age, national origin, or disability.
If you require any further details on the role please contact Professor Azra Ghani at (HIDDEN TEXT).
Qualifications
A PhD in infectious disease epidemiology, mathematical modelling, statistics or related subject or a similar quantitative discipline Experience in mathematical modelling methods used to analyse infectious diseases Strong programming skills, ideally with experience in R/R packages and GitHub as a collaborative coding environment An ability to communicate technical scientific results verbally and in written formats to an interdisciplinary team. The ability to work effectively independently and as part of a team. Ability to interact with policy makers and other stakeholders. Excellent verbal and written communication skills Track record of publication in peer-reviewed journals commensurate with experience
More Information
Location: Kent Ridge Campus
Organization: Saw Swee Hock School of Public Health
Department : Saw Swee Hock School of Public Health
Employee Referral Eligible: No
Job requisition ID : 30141