Pre-Doctoral Research Fellow in International Trade, Industrial Organization, Urban/Spatial Economics

The Tuck School of Business at Dartmouth invites applications for a fulltime PreDoctoral Research Fellow to work on projects in industrial organization, international trade, and urban/spatial economics. The fellow will work with Professors Anais Galdin and Felipe Barbieri on empirical projects using large microdata to study firm behavior, market structure, and the spatial distribution of economic activity, with applications including global supply chains, digital platforms, and housing markets (see www.anaisgaldin.com and www.felipebarbieri.com).

This position is designed for individuals interested in pursuing a PhD in economics or a closely related field. It offers intensive training in empirical research using large and complex datasets and exposure to all stages of the research process. The fellow will have the opportunity to attend the research seminars of Dartmouth's Globalization cluster.

The fellow will:

• Clean, construct, and merge large micro datasets (administrative, transactionlevel, geospatial, and webscraped data) using Stata and/or R.
• Implement and maintain reproducible codebases, including clear documentation, version control, and replication packages.
• Conduct empirical analysis, including descriptive statistics, reducedform econometrics, and, where appropriate, structural estimation.
• Produce data visualizations, tables, and figures for working papers, presentations, and reports.
• Conduct literature reviews and background research for ongoing and new projects.
• Contribute to drafting and editing research papers, memos, and presentations.

Appointment details

• Fulltime, inperson position based at the Tuck School of Business in Hanover, New Hampshire.
• Preferred start date in summer 2026 (July or August 2026; exact date negotiable).
• The appointment is for one year with the possibility of an additional year's extension.
• Competitive salary and benefits through Dartmouth College. The salary for this position is $60,000.
• The position will be eligible for visa sponsorship, subject to Dartmouth policies and applicable U.S. law; international candidates are encouraged to apply.

Dartmouth is committed to academic excellence and encourages the open exchange of ideas within a culture of mutual respect. Dartmouth welcomes people with different backgrounds, life experiences, and perspectives and believes that diversity in all its forms enhances academic excellence.

Qualifications

Minimum requirements

• Completion of a bachelor's or master's degree by the start date in economics, computer science, statistics, applied mathematics, or a closely related field.
• Substantial coursework in economics and econometrics; significant exposure to quantitative methods is required.
• Demonstrated strong programming ability in Stata and/or R (through coursework, RA work, internships, or independent projects).
• Some familiarity with LaTeX for preparing research documents.
• Prior experience with empirical research using data (e.g., research assistantships, thesis, or independent research project).
• Strong quantitative skills, attention to detail, and ability to work independently as well as in a small research team.

Preferred additional skills

• Additional coursework in computer science, data science, or machine learning.
• Experience working with large and/or unstructured datasets (e.g., administrative, transactionlevel, scraped, or geospatial data).
• Familiarity with at least one of: Python, SQL, Julia, or similar languages is a plus, but not required; experience with Git or other versioncontrol systems is a plus.
• Interest in one or more of: empirical industrial organization, international trade, urban/housing/transportation economics, or related applied micro fields.
• A longterm interest in pursuing a PhD in economics, applied economics, or a related quantitative discipline.

Please submit the following materials via Interfolio: https://apply.interfolio.com/181447

1. Cover letter (1-page max)
2. Curriculum vitae (CV)
3. Academic transcript(s) (unofficial copies are acceptable at the initial stage).
4. Reference: Contact information for at least one academic or professional reference who can speak to your research and coding skills. Preferred referees include faculty who have supervised you as a research assistant or thesis advisor, as well as professional supervisors from data or codingintensive roles. Letters will be requested for shortlisted candidates.

Review of applications will begin in February 2026 and will continue until the position is filled.

Questions about the position may be directed to Professors Anais Galdin (anais.galdin@dartmouth.edu) and Felipe Barbieri (felipe.barbieri@dartmouth.edu).