Elite Impact
Regional
Exceptional Value
Experience Required: Introductory
Appropriate for students with limited/no experience in subject
Program Cost
Tuition Free
Duration
8 Weeks
Location
Chicago, IL
Format
In-person
Cohort Size
Undisclosed
Eligibility
Rising Freshmen, Sophomores, Juniors, Seniors
Year Established
2018
Category
CS, Environmental Science
The University of Chicago Data Science Institute (DSI) Summer Lab is an immersive, eight-week paid summer research program that places students inside active data science research environments. While open to both undergraduates and high schoolers, high school applicants must live and attend school in the Chicago area. The 2026 internship runs from June 15 to August 7, pairing students with mentors in domains ranging from computer science and energy policy to materials science and biomedical research.
Participants work a full-time schedule (9:00 AM – 5:00 PM) alongside faculty and graduate students on real-world, data-driven projects. The program functions as a cohort experience, featuring a weekly speaker series and professional development workshops that focus on scientific communication and technical skill-building. The summer culminates in a professional research symposium where students present their final deliverables to the DSI community.
Admission is highly competitive. For the 2026 cycle, applications were due by January 12, 2026, with decisions expected in March. Eligible high schoolers include current freshmen through seniors who can commute to the Hyde Park campus. While no prior research experience is required, the institute recommends familiarity with a programming language like Python, Java, or C++. High school participants receive a $5,600 stipend for the summer but are responsible for their own housing and transportation.
By bridging the gap between classroom theory and professional practice, the DSI Summer Lab provides a substantive early immersion into the methodologies and ethics of modern data science.
Summer Lab alumni have contributed to published papers, created software tools with broad use, and pursued advanced research paths — and many students continue working with their mentor after the program ends.
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