Postdoctoral Fellow-MSH-76880-041

Mount Sinai; United States; On-site; USD 60,000 - 90,000; Full time

Job summary

The Icahn School of Medicine at Mount Sinai in New York invites applications for a full-time Postdoctoral Fellow to advance NIH-funded ASPIRE research on adolescent cardiovascular health and later maternal outcomes. You will build long-term agent-based models, work with a multidisciplinary team, and contribute to policy-relevant population health insights.

Collaborators include epidemiologists, qualitative researchers, community partners, and school health colleagues; opportunities exist for

Qualifications

• PhD or equivalent in a quantitative field (Systems Science, Epidemiology, Biostatistics, or related).
• Experience developing agent-based, microsimulation, or system dynamics models.
• Strong programming skills in NetLogo and/or R or Python.
• Excellent quantitative, analytic, scientific writing skills.
• Ability to work independently within a multidisciplinary team.
• Interest in adolescent health, health equity, and policy-relevant population health research.

Responsibilities

• Develop and implement agent-based models of health trajectories using NetLogo or similar platforms.
• Translate longitudinal analyses and qualitative results into model structure and policy scenarios.
• Simulate interventions to estimate effects of school policies on adolescent and maternal health.
• Calibrate, verify, validate, and perform uncertainty analyses.
• Document model assumptions and implementation using reporting frameworks like ODD and TRACE and ISPOR/SMDM guidance.
• Develop reproducible workflows and maintain version-controlled code.
• Contribute to manuscripts, abstracts, presentations, and policy-facing products.
• Participate in meetings with investigators, advisors, adolescents, school stakeholders, and community partners.

Skills

Agent-based models

Programming in NetLogo/R/Python

Scientific communication

Independent work in multidisciplinary팀

Education

PhD in Systems Science or related field

Tools

NetLogo

R

Python

Job description

Job Title: Postdoctoral Fellow -Quantitative Analysis & Systems Science

Department: Population Health Science & Policy, Icahn School of Medicine at Mount Sinai

Position Summary/Overview

The Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai is seeking 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 project examines how school environments and policies shape adolescent cardiovascular health and future maternal health outcomes. Working with Dr. McCarthy and a multidisciplinary team-including systems science investigators, epidemiologists, qualitative researchers, community stakeholders, and collaborators at the New York City Office of School Health-the fellow will conduct longitudinal analyses of school environmental features, adolescent cardiovascular health trajectories, and later maternal health outcomes. The fellow will integrate these findings with published evidence and participatory group model-building results to develop, implement, calibrate, validate, and apply empirically grounded agent-based models. These models will estimate the long-term population health and health equity effects of school-based interventions and help identify strategies to improve cardiovascular health across the life course. This position offers opportunities for manuscript publication, conference presentations, interdisciplinary collaboration, and mentorship in systems science, adolescent cardiovascular health, maternal health, implementation science.

The ideal candidate will be:

• 1) highly motivated and intellectually curious;
• 2) experienced in computational or simulation modeling;
• 3) an effective scientific communicator;
• 4) organized and detail-oriented;
• 5) able to work independently while collaborating within a multidisciplinary team;
• 6) committed to reproducible, policy-relevant population health research.

Essential Duties and Responsibilities:

1. Develop and implement agent-based models of adolescent cardiovascular health trajectories and later maternal health outcomes using NetLogo or a comparable simulation platform.
2. 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.
3. Simulate intervention and counterfactual scenarios to estimate the effects of school-based policies on adolescent cardiovascular health, maternal morbidity, and racial/ethnic disparities.
4. Conduct model calibration, verification, validation, uncertainty analysis, and sensitivity analysis.
5. Document model assumptions, structure, and implementation using established reporting frameworks such as ODD and TRACE and relevant ISPOR/SMDM guidance.
6. Develop reproducible workflows, maintain well-documented code, and use version control platforms such as GitHub.
7. Contribute to collaborative manuscripts, abstracts, conference presentations, and policy-facing products.
8. Participate in meetings with investigators, advisory board members, adolescents, school stakeholders, and community partners to refine model assumptions and interpret results.

Qualifications:

• Doctoral degree 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, such as R or 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 who are 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 pr