Senior Research Fellow – Infectious Disease Modelling & AI for Public Health

About the Position

The Centre for Epidemic Response & Modelling (CERM) at the Saw Swee Hock School of Public Health within the National University of Singapore is seeking a Senior Research Fellow. This position will contribute to pioneering research at the crossroads of Bayesian infectious disease modelling, artificial intelligence in epidemic forecasting, genomic epidemiology, and strategies for pandemic preparedness. The successful applicant will collaborate with multidisciplinary teams across leading institutions and agencies, both in Singapore and internationally.

Role Overview & Key Responsibilities

• Drive and independently execute impactful research projects in areas such as Bayesian genomic epidemiology, AI-powered epidemic forecasting, and surveillance of arboviruses using genomic data.
• Develop and publish advanced statistical and computational methodologies in reputable journals, as well as share findings at global conferences.
• Provide direction and day-to-day mentorship to members of the research team, ranging from fellows to research assistants.
• Lead applications for research funding, prepare progress reports, and manage relationships with external partners and sponsoring agencies.
• Represent the research group at both national and international events, enhancing networks with academic and public health stakeholders.
• Contribute to curriculum development and offer support for relevant graduate-level coursework at the School of Public Health.

Qualifications & Experience

• A PhD in statistics, biostatistics, computational biology, epidemiology, computer science, or a closely aligned discipline.
• At least two years of postdoctoral experience in a relevant scientific area.
• Proven expertise in Bayesian inference and probabilistic modelling, with hands-on experience using platforms such as Stan, PyMC, NumPyro, or Turing.
• A strong portfolio of peer-reviewed publications proportional to career stage.
• Proficiency in Python and/or R; experience with high-performance and cloud-based computing resources.
• Background in at least two of the following domains: phylodynamics/genomic epidemiology, deep learning for biological or tabular data, reinforcement learning, spatial models, or real-time epidemic nowcasting.
• Experience supervising junior staff and leading or supporting grant proposals.
• Excellent communication skills suitable for cross-disciplinary collaboration with scientific, clinical, and policy-oriented stakeholders.

Application Instructions

• Submit a cover letter detailing your motivation, experience, and future research goals.
• Provide a comprehensive CV with a complete publication list.
• Include a research statement (up to two pages) summarizing previous work and planned research directions.
• List two professional references (letters may be requested later).

Additional Information

• The group offers strong career development support, including opportunities for conference attendance, workshops, and mentorship from both internal and international partners.
• Review of applications will continue until the position is filled. Flexible start date is negotiable.