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Summer High School Internship Program (SHIP)
The 2026 SHIP vacancy announcement is OPEN! Apply here!
- Applications are due by 11:59 pm ET on January 26, 2026
- 2026 SHIP Dates: June 22 - Aug 7, 2026
- Students interested in science can spend their summers in our labs at the Boulder, CO, or the Gaithersburg, MD, campuses through NIST’s Summer High School Intern Program (SHIP). Students learn from top scientists at NIST and work on your own research project.
- SHIP is a seven-week, unpaid educational internship.
- The program runs annually from mid-June to early August. Actual dates vary each year.
- Learn more about the deadlines in our application page.
Eligibility and Requirements
- U.S. citizenship
- High school junior or senior at time of application
- Minimum unweighted GPA of 3.0 on a 4.0 scale
- Desire to participate in scientific research
- Commit to the full seven-week program
- Applicants MUST have a permanent residence within a 50-mile radius of their host campus (NIST Boulder or NIST Gaithersburg)
- Students and their parent(s)/guardian(s) must provide their own housing and transportation
- No exceptions allowed
What You’ll Get
This competitive volunteer program will give you the chance to participate in cutting-edge research at NIST and work with our staff scientists and engineers on a research problem. Learn about previous SHIP students’ research projects for more information.
How to Apply
Applications generally open on November 1 and close in last week of January of the following year. Learn more about the application process.
Helpful (but Not Required) Skills for SHIP Students
- Python
- Physics
- Electronics
- LabView
- AutoDesk Inventor
- Java
- AI knowledge generation
- SQL server
- SQL Stored Procedures
- Visual Studio
- Web development
- Next generation computing
- Chemistry (basic)
- Math
- Computer programming
Stories from our SHIP Students
- Reaching for the Stars: My Summer Internship Learning About Spectroscopy in Space and on Earth
- Solving a Robotics Puzzle During a Summer Internship at NIST
- A semi-supervised deep-learning approach for automatic crystal structure classification (Research Paper)
Contact Us
ship [at] nist.gov (ship[at]nist[dot]gov)