Overview

Faculty in the department have active research programs that involve students during the academic year and summer. Summer research positions are open to Carleton students and are paid positions.

The faculty research projects for the Summer of 2026 that have positions open for students are described below. Direct any questions you have about a project to the faculty running the project. The student stipend rate for the Summer of 2026 is $580/week. A list of all science research opportunities and fellowships at Carleton College is also available.

If you would like to apply, please fill out out this application form by 11:59 pm on February 15, 2026. You will be asked to list the project(s) of interest to you and provide an unofficial transcript. The number of students hired for each project is dependent on funding which is likely, but not certain, so the number of students ultimately hired for each project could change.

Summer 2026 Project Descriptions

Finalizing Models in Spatial Statistics for Complex Policing and Social Science Applications (Claire Kelling)

  • 2-3 students
  • 40 hours per week, June 15- August 28 (8-10 weeks of work. Dates are flexible but students will need to be on the same approximate timeline. This will be coordinated during the interview process.)
  • Mode: remote (students must be located in the United States). Students can be located in Northfield if desired, but meetings will often be virtual.

Description: Pressing research questions relevant to public policy and the social sciences often require the analysis of complex datasets to fully answer substantive questions designed to better understand social phenomena. For example, community members often have the desire to understand how they are being policed, and these questions often involve complex statistical and computational methods to answer them completely and accurately. In summer 2026, we will work to finalize two projects using methods in spatial statistics to analyze policing data. In the first, we will finalize an R package and corresponding paper in spatial privacy, where we introduce and evaluate methods to protect the exact original locations of policing events. If time allows, we will also continue to develop a space-time model for relating two point-level datasets (point processes), such as police use of force and police stops. Both of these projects are computationally intensive, so interest and comfort in coding in R is required. The projects will also involve collaborative writing of papers for peer-reviewed publication(s).

Required prerequisites for this summer research project are: Introduction to Data Science and Statistical Inference. A 300-level elective is a preferred prerequisite. Please reach out to Claire Kelling if you do not meet these requirements or with any questions about this opportunity!

Mapping Cultural Institutions in the United States (Emily Kurtz)

  • 2-4 students
  • 40 hours per week, 5 weeks (June 9 – July 14)
  • Mode: Hybrid, but primarily in person, especially in the beginning weeks

Background: People’s lived environments – the stores they shop at, the statues they walk by, etc. – influence and reflect many parts of their communities. The New York Times illustrates this idea well. If you live in an area with many breweries, your neighbors probably voted more for Joe Biden in 2020, but if there are lots of golf courses around your neighborhood, your community likely supported Donald Trump. Of course, these patterns could be explained by many things completely unrelated to politics. For example, you can only develop a golf course if there’s enough land for one, and there’s more likely to be an abundance of land in rural areas, which tend to be more conservative. Where things become more interesting is when these built features directly reflect something about a community’s history, values, or culture. Things like monuments, statues, museums, and even specific types of buildings (things I call “cultural institutions”) are often built with this reflection goal in mind.

Project: The purpose of this project is to create a database of cultural institutions (similar to the part of the Overture Maps Foundation database that NYT article references) that researchers across many disciplines may be able to use to explain a wide range of cultural, social, political, health, or other community-level phenomena. Specific types of these cultural institutions are available on the internet in a variety of places. For example, the Monument Lab has compiled and mapped a dataset of hundreds of thousands of monuments across the country, and there are websites listing museums across the country. As a team, we will find as many potential sources like these, use web scraping or other data science methods to retrieve them, and compile them into a clean, user friendly database. In addition, we will develop a website to host this database and, if time permits, develop a Shiny app around the data to enable easier exploration of the data.

Prerequisites: Stat 220 preferred and knowledge of GIS helpful. Please reach out to Emily Kurtz if you do not meet these requirements.

What Works in Education? (Adam Loy)

  • 2 students
  • 40 hours per week (Anticipated Timeline: 8 weeks, June 15 – August 7)
  • Mode: Primarily in-person

Description: I am looking for two students interested in data wrangling and visualization to work on an entry for the 2026 Data Challenge Expo sponsored by the American Statistical Association. A snippet from the website if given below:

Participants in this 2026 Data Expo Challenge will develop a research question to explore, analyze, and visualize the What Works Clearinghouse (WWC) comprehensive research database. This dataset represents the U.S. Department of Education’s historical commitment to transparency and evidence-based education policy. The dataset contains details about the design and findings from over 13,000 studies. The multi-level data structure provides individual findings nested within studies and intervention reports, accompanied by comprehensive research quality indicators including WWC standards ratings, evidence tiers, and effect sizes.

The dataset encompasses all major educational domains and grade levels, representing studies conducted across all U.S. states and regions with rich contextual data that helps answer the critical question of “what works for whom and under what conditions.”

The focus of this project is to craft compelling statistical and data visualizations to communicate your findings. You will present your findings at the 2026 Joint Statistical Meetings (JSM) in Boston, Massachusetts between August 2 and 6. Your presentation will require a 4-minute lightning talk followed by a poster presentation.

Prerequisite: Stat 220