Research Associate: AI‑Driven Epidemic Forecasting & Public Health

National University of Singapore; Singapore; On-site; SGD 54,000 - 71,000; Full time

Job summary

National University of Singapore's Saw Swee Hock School of Public Health invites applications for a Research Associate/Assistant in Infectious Disease Modelling & AI for Public Health. The role supports AI-driven epidemic forecasting, transmission modelling in ASEAN, and collaboration across epidemiology, biostatistics, and data science teams.

The successful candidate will work on hands-on modelling, data analysis, and contribute to manuscripts and dashboards, with opportunities to pursue higher

Qualifications

• Master's degree with two years of relevant work experience or Bachelor's with strong analytical training.

Responsibilities

• Implement and test statistical and computational models for infectious disease dynamics.
• Process, clean, and analyse large-scale epidemiological, genomic, and mobility datasets.
• Develop data visualisation tools and contribute to interactive surveillance dashboards.
• Support the preparation of manuscripts, reports, conference presentations, and workshops.
• Collaborate with internal team members and external partners across institutions and countries.
• Contribute to code documentation and reproducible research workflows.

Skills

Bayesian inference

Machine learning

Python

R

Scientific communication

Teamwork

Data visualization

Education

Master's degree in statistics, epidemiology, computer science, bioinformatics, computational biology, biostatistics, or related

Bachelor's degree with strong analytical training

Tools

Stan

PyMC

NumPyro

PyTorch

JAX

Job description

National University of Singapore's Saw Swee Hock School of Public Health invites applications for a Research Associate/Assistant in Infectious Disease Modelling & AI for Public Health. The role supports AI-driven epidemic forecasting, transmission modelling in ASEAN, and collaboration across epidemiology, biostatistics, and data science teams.

The successful candidate will work on hands-on modelling, data analysis, and contribute to manuscripts and dashboards, with opportunities to pursue higher