David Broniatowski
4 days ago
Research Associate/Assistant in Economics of Community Resilience at George Washington University George Washington University in United States
Degree Level
not provided
Field of study
Disaster Resilience
Funding
Available
Country
United States
University
George Washington University

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About this position
The George Washington University, in collaboration with the National Institute of Standards and Technology (NIST), is seeking a highly motivated Research Associate/Assistant for the Professional Research Experience (PREP) program. This position is based in the Applied Economics Office (AEO) at NIST and focuses on research related to Community Resilience and the economic impacts of disruptive events such as hurricanes Maria and Fiona in Puerto Rico.
Key responsibilities include supporting investigations into the economic consequences of natural disasters, developing methods to evaluate the impacts of disruptive events and persistent stressors, analyzing consumer preferences for product labeling, and evaluating stakeholder perceptions regarding future event uncertainty. The role requires strong skills in Stata for causal analysis, Excel for handling large-scale data, and LaTeX (Overleaf) for technical documentation. Experience with Large Language Models (LLMs) is also essential.
Applicants must hold a Bachelor's degree in Economics, be U.S. citizens, and have at least one year of relevant research experience. A strong publication record, including at least one peer-reviewed and one first-author technical publication, is required. This opportunity is ideal for early-career economists passionate about disaster resilience and economic analysis.
For more information and to apply, visit the application link provided. The position offers a unique chance to contribute to impactful research at the intersection of economics and community resilience.
Funding details
Available
What's required
Applicants must have a Bachelor's degree in Economics, be a U.S. Citizen, and possess at least one year of relevant research experience. Required skills include proficiency in Stata for causal analysis, Excel for large-scale data, and LaTeX (Overleaf). Candidates must have at least one peer-reviewed publication and one first-author technical publication. Experience working with Large Language Models (LLMs) is required.
How to apply
Apply through the provided application link. Ensure you meet all qualifications before submitting your application. Prepare your CV and publication record. Contact the program if you have questions.
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