Postdoctoral Fellow-MSH-76880-041

Mount Sinai; New York (NY); Hybrid; USD 65,000 - 90,000; Full time

Job summary

Mount Sinai invites applications for a full-time Postdoctoral Fellow in Quantitative Analysis & Systems Science within the Population Health Science & Policy department of Icahn School of Medicine at Mount Sinai.

The role focuses on NIH-funded ASPIRE and involves developing and calibrating agent-based models to study school-based interventions on adolescent cardiovascular health and later maternal health outcomes.

Qualifications

• PhD, ScD, DrPH, or equivalent doctoral degree in a relevant quantitative or population health discipline.
• Experience developing agent-based, microsimulation, system dynamics, or other complex simulation models.
• Strong programming skills in NetLogo and/or R or Python.
• Strong written and oral communication skills; ability to work in a multidisciplinary team.
• Interest in adolescent health, cardiovascular disease prevention, or health equity.

Responsibilities

• Develop and implement agent-based models of adolescent cardiovascular health trajectories.
• Translate findings from analyses and literature into model structure and policy scenarios.
• Simulate interventions to estimate effects of school policies on health disparities.
• Conduct calibration, verification, validation, and uncertainty analyses.
• Document model assumptions and use reporting frameworks like ODD and TRACE.
• Maintain reproducible workflows and version-controlled code.
• Contribute to manuscripts, abstracts, and policy-facing products.
• Participate in meetings with investigators, stakeholders, and community partners.

Skills

agent-based models

NetLogo

R

Python

system dynamics

microsimulation

longitudinal analyses

Education

PhD/DrPH/ScD in quantitative field

equivalent doctoral degree

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.

Responsibilities

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; and 6) committed to reproducible, policy-relevant population health research.

Essential Duties And 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 the 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 established 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 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 professional academic research environment and requires routine use of computers, statistical and simulation software, videoconferencing platforms, and standard office equipment. The role may include hybrid work arrangements consistent with institutional and departmental policies, as well as occasional in-person meetings with research and community partners.

Employer Description

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual