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"Postdoctoral Fellowship Opening: Applied Causal Inference for the Social and Behavioral Sciences"

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Postdoctoral Fellowship Opening: Applied Causal Inference for the Social and Behavioral Sciences

Postdoctoral Fellow

Open until filled (review begins February 1)

Location

Baltimore, MD

Johns Hopkins University

Type

Full Time Postdoctoral Fellowship

Start Date

April to September 2026

Salary

$65,000-$75,000 per year

Teaching Load

Strong interest in teaching causal inference topics and developing short courses

Required Qualifications

PhD in biostatistics, statistics, economics, health policy, or quantitative field
Knowledge of <strong>causal inference</strong> methods
Experience with <strong>Stata</strong> or <strong>R</strong>

Research Areas

Applied Causal Inference
Policy Evaluation Methods
Implementation Science
Mental Health Policies and Services
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Postdoctoral Fellowship Opening: Applied Causal Inference for the Social and Behavioral Sciences

Requisition #: A-181359-4

School: Bloomberg School of Public Health

Location: Baltimore, MD

Position Type: Postdoctoral Fellowship

Shift Type: Full Time

Salary Range: $65,000-75,000 per year

Closing Date: Open until filled

To apply: https://dossier.interfolio.com/apply/181359

General Description

Postdoctoral fellowship opening to work on applied causal inference under the direction of Dr. Elizabeth Stuart, in collaboration with Dr. Beth McGinty and colleagues at Johns Hopkins and Weill Cornell. Projects will include policy evaluation methods and application, and methods of relevance for implementation science and the work of the ALACRITY Center for Health and Longevity in Mental Illness. Strong candidates also have a strong interest in teaching causal inference topics to broad audiences, including potential development of short courses and other trainings to introduce causal inference topics to individuals without a methodological background. Work will include methods development as well as applications of advanced statistical methods in public health and medicine, and will involve collaboration with other faculty in Biostatistics and the School of Public Health. A key focus of the work will be collaboration with researchers at Weill Cornell conducting evaluations of mental health policies and services. 

Responsibilities will include statistical collaboration, methods development, methodological literature reviews, simulation studies, educational activities, data management and analyses, manuscript writing for journal publications, and presentations at scientific meetings. Individuals with training in quantitative methods, including Statistics, Biostatistics, Economics, Epidemiology, and Health Policy are welcome to apply. Knowledge of causal inference methods and experience with statistical software such as Stata or R is required. Applicants will join a collegial and interdisciplinary team, and communication and collaboration skills are highly valued.  

Successful candidates will receive competitive salaries (in the range $65,000-$75,000), as well as computing resources, travel support, and other benefits in accordance with departmental and university policies. Application review will begin February 1, and applications will be considered until the position is filled. The position can start any time from April to September 2026. The initial appointment is for one year, with reappointment for a second year provided satisfactory performance.  

Qualifications

PhD in biostatistics, statistics, economics, health policy, health economics, or other quantitative field

Application Instructions

Interested applicants should submit the following materials via Interfolio:

  • Cover letter 
  • Curriculum vitae
  • 2 reference letters 

Questions about the position can be directed to Dr. Stuart (https://www.elizabethstuart.org; estuart@jhu.edu). 

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

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