Postdoctoral Fellow

Job Title: Postdoctoral Fellow Adolescent Health, Maternal Health and 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, and community stakeholders, 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; and 6) committed to reproducible, policy-relevant population health research.

Qualifications

• Doctoral degree in Systems Science, Epidemiology, Public Health, Biostatistics, Statistics, Applied Mathematics, Computer Science, or a related quantitative field.
• 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.

Location: New York,
Job Type: Full-time

Contact

Contact: Katharine J McCarthy
Phone: View phone number on click.appcast.io
Email: View email address on click.appcast.io
Website: