Postdoctoral Fellow-MSH-76880-041

About the role

The Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai seeks a full‑time Postdoctoral Fellow to work with Dr. Katharine McCarthy on the NIH‑funded ASPIRE (Adolescent School Policy Interventions for caRdiovascular Equity) study. The fellow will conduct longitudinal analyses of school environmental features, adolescent cardiovascular health trajectories, and later maternal health outcomes, and will develop, calibrate, validate, and apply agent‑based models to estimate long‑term population health and health‑equity effects of school‑based interventions.

Responsibilities

• Develop and implement agent‑based models of adolescent cardiovascular health trajectories and later maternal health outcomes using NetLogo or a comparable simulation platform.
• Translate findings from longitudinal epidemiologic analyses, qualitative research, participatory group model‑building, and the scientific literature into model structure, assumptions, decision rules, and policy scenarios.
• Simulate intervention and counterfactual scenarios to estimate effects of school‑based policies on adolescent cardiovascular health, maternal morbidity, and racial/ethnic disparities.
• Conduct model calibration, verification, validation, uncertainty analysis, and sensitivity analysis.
• Document model assumptions, structure, and implementation using reporting frameworks such as ODD and TRACE and relevant ISPOR/SMDM guidance.
• Develop reproducible workflows, maintain well‑documented code, and use version‑control platforms such as GitHub.
• Contribute to collaborative manuscripts, abstracts, conference presentations, and policy‑facing products.
• Participate in meetings with investigators, advisory board members, adolescents, school stakeholders, and community partners to refine model assumptions and interpret results.

Qualifications

• Doctoral degree (PhD, ScD, DrPH, or equivalent) in Systems Science, Computational Social Science, Epidemiology, Public Health, Biostatistics, Statistics, Applied Mathematics, Operations Research, Engineering, Computer Science, or a related quantitative field.
• Demonstrated experience developing agent‑based models, microsimulation models, system dynamics models, or other complex simulation models.
• Strong programming skills in NetLogo and/or another relevant language or platform (e.g., R, Python).
• Strong quantitative, analytic, scientific writing, and oral communication skills.
• Ability to work proactively and independently while contributing effectively to a multidisciplinary research team.
• Interest in adolescent health, cardiovascular disease prevention, maternal and child health, school policy, implementation science, or health equity.

Preferred Experience

• Experience working with longitudinal, multilevel, administrative, electronic health record, or other large population‑based datasets.
• Familiarity with causal inference, multilevel modeling, life‑course epidemiology, or health policy evaluation.
• Experience integrating qualitative or stakeholder‑engaged findings into computational models.
• Peer‑reviewed publication record demonstrating independent scientific productivity.
• Experience with collaborative software development, code review, and open or reproducible science practices.

Education and Experience

PhD, ScD, DrPH, or equivalent doctoral degree in a relevant quantitative or population‑health discipline. Candidates completing their doctoral degree may be considered if all degree requirements will be completed before the start date.

Work Environment

This position operates in a professional academic research environment and requires routine use of computers, statistical and simulation software, videoconferencing platforms, and standard office equipment. Hybrid work arrangements are possible in line with institutional policies, with occasional in‑person meetings with research and community partners.

Compensation

The salary range for this role is $72,500 – $80,000 annually. Actual salary depends on experience, education, and operational need; the range does not include bonuses, differential pay, or other forms of compensation or benefits.