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National University Of Singapore

Senior Research Fellow (Infectious Disease Modelling & AI for Public Health)

2-4 Years
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Job Description

Job Title: Senior Research Fellow (Infectious Disease Modelling & AI for Public Health)

University-Level Unit: Saw Swee Hock School of Public Health

Faculty/Department-Level Unit: Saw Swee Hock School of Public Health

Employee Category: Research Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 16/04/2026

Job Description

About the Role

The Centre for Epidemic Response & Modelling (CERM) at NUS Saw Swee Hock School of Public

Health invites applications for a Senior Research Fellow to help lead a vibrant, internationally

connected research programme spanning Bayesian infectious disease modelling, AI-driven

epidemic forecasting, genomic epidemiology, and pandemic preparedness. The postholder will

work with Asst. Prof. Swapnil Mishra (Deputy Director, CERM and AI for Public Health Programme)

and engage an active network of collaborators spanning CERM, NUS, Imperial College London,

Ashoka University, the Communicable Diseases Agency Singapore (CDA), the National

Environment Agency Singapore (NEA), the Machine Learning & Global Health Network (MLGH),

and wider regional and global partners.

This is a senior scientific role with significant autonomy. The successful candidate is expected to

drive independent research streams, provide intellectual leadership across multiple concurrent

grants, and mentor junior researchers. The portfolio spans methodological innovation and applied

public health impact, including real-time surveillance platforms, lineage transmissibility models, AIpowered

decision-support tools, and equitable AI for Public Health in Asian settings.

Key Responsibilities

  • Lead and independently execute high-impact research across one or more of the group's

active programmes: Bayesian genomic-epidemiological modelling, AI for epidemic

forecasting, and arbovirus genomic surveillance.

  • Design novel statistical and computational methodologies and publish them in leading

journals and present at international conferences.

  • Provide scientific leadership and day-to-day mentorship to Research Fellows, Research

Associates, and Research Assistants.

  • Take a leading role in grant writing, progress reporting, and engagement with funding

agencies and public health partners.

  • Represent the group at national and international conferences; build and sustain

collaborative networks.

  • Contribute to curriculum and teaching support for relevant graduate courses at SSHSPH.

Additional Opportunities

The group actively supports career development through conference travel, training workshops, and mentorship from senior researchers and international collaborators.

Qualifications

  • PhD in statistics, biostatistics, computational biology, epidemiology, computer science, or a

closely related discipline.

  • Minimum of two years of postdoctoral experience.
  • Demonstrable expertise in Bayesian inference and probabilistic modelling; experience with

Stan, PyMC, NumPyro, Turing, or equivalent PPLs.

  • Strong track record of publications in peer-reviewed journals commensurate with career stage.
  • Proficiency in Python and/or R; familiarity with high-performance and cloud computing environments.
  • Experience in at least two of: phylodynamics / genomic epidemiology, deep learning for sequence or tabular data, reinforcement learning, spatial modelling, or real-time nowcasting.
  • Demonstrated ability to supervise junior researchers and contribute substantively to grant applications.
  • Excellent written and oral communication skills; ability to engage clinical, public health, and policy audiences.

Interested Applicants Should Submit The Following Documents

  • A cover letter explaining your interest in the position, relevant experience, and research vision.
  • A comprehensive curriculum vitae, including a full list of publications.
  • A research statement (maximum two pages) outlining past contributions and future directions.
  • Contact information for two professional references (letters may be requested).

Review of applications begins immediately and continues until the position is filled. The anticipated start date is flexible by negotiation.

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Job ID: 148614213