Researcher, Population Simulation

What you'll do

• Develop methods and pipelines to synthesize agents from profile data and produce accurate population-level distributions.
• Ground agent behavior in real-world data and design architectures combining LLMs with computational social science, psychometrics, and survey methods.
• Evaluate simulations against ground-truth data and iteratively reduce gaps between simulated and observed behavior.

What they ask for

• Deep experience with synthetic data generation, agent-based modeling, computational social science, or population simulation.
• Interest in using LLMs to produce structured behavioral outputs that withstand statistical scrutiny.
• PhD in ML, computational social science, cognitive science, statistics, psychometrics, or a quantitative field—or equivalent depth from industry research.
• Clear communication and ability to work quickly while maintaining rigor.

Nice to have

• Built systems that generate or evaluate synthetic populations at scale; experience with survey methodology, psychometrics, or demographic modeling.
• Published work on agent-based simulation, synthetic data, or LLM-based behavioral modeling; experience in a high-velocity research environment.

Tools

LLMs, GSS

AI focus

Uses LLMs in hybrid simulation architectures to generate structured behavioral outputs for realistic synthetic populations.