AIMMLab • Postdoctoral Opportunities
AIMMLab • Postdoctoral Fellows

Join AIMMLab as a Postdoctoral Fellow

Thank you for your interest in joining AIMMLab. We are actively recruiting passionate postdoctoral fellows with strong quantitative abilities and a deep motivation to tackle novel challenges in health, ecology, and environmental management. If our scientific interests overlap and you’d like to join us, please email jude.kong@utoronto.ca.

Essential Qualities

  • Impact-driven motivation
    A significant drive to effect change in health, ecology, or environmental management.
  • Mathematical proficiency
    Equivalent to (or beyond) an undergraduate minor in mathematics.
  • Programming ability
    Proficient in Python, R, or related languages.
  • Excellent communication
    Clear writing and speaking across diverse, interdisciplinary teams.

Research Areas (examples)

Areas of work include, but aren’t limited to, the following:

  • AI-driven visualization & analytics for policy
    Design tools that translate complex data into actionable insights for decision-makers.
  • Now-casting & forecasting of epidemic waves
    Short-term prediction of COVID-19 and other diseases to inform healthcare planning.
  • Early outbreak dynamics & community spread
    Characterize initial transmission prior to non-pharmaceutical interventions (NPIs).
  • Mathematical models to evaluate NPIs
    Quantify effects of home quarantine, social distancing, tracing apps, testing & isolation on epidemic trajectories and healthcare demand.
  • Vaccination & NPIs
    Determine how vaccination alters NPI uptake needed for post-vaccine waves.
  • Economic-epidemiological integration
    Develop models that couple transmission dynamics with economic outcomes for policy analysis.
  • Spatial spread & hotspot analysis
    Local outbreak simulation (including informal settlements) and identification of vulnerable areas.
  • Setting-specific analyses
    Households, hospitals, and other contexts using statistical & mathematical methods.

© AIMMLab — Artificial Intelligence & Mathematical Modelling Lab • University of Toronto