The challenge

You'll solve an exciting problem in space security! Participants in the 2025 Data Science Challenge will work on exciting problems in ground-based optical sensing, which impact important astronomy and space domain awareness results. Ground-based optical systems (e.g., telescopes and sensors) are used to understand what our universe is made of (through taking images of stars and galaxies) and for space traffic management (through tracking satellites to understand collision risk). However, the precision and accuracy of measurements from these images relies on telescope and sensor performance, which quickly become computationally expensive. This year’s Challenge will explore techniques in image classification and parameter prediction to understand data from real images of stars and simulated images of satellites.

Check out news coverage of the 2024 Data Science Challenge!

What it takes

• Undergraduates interested in data science or related disciplines
• Graduate students experienced in research or applying skills to a research environment
• Students actively pursuing a degree in mathematics, computer science, engineering, science, or other relevant fields
• Students with computational experience

What to expect

Don’t miss this unique opportunity! The experience will be unlike any other. Read about DSC mentors and past Challenges.

This intensive 2-week full-time program provides challenging exercises and assignments, tours, and seminars. For 2 weeks, you’ll work on an important data science problem while learning from experts, networking with peers, and developing skills for future internships. You’ll also get a taste of day-to-day life at LLNL, where we have a passion for national service. The Challenge will take place in Livermore with a stipend provided.

Team members will:

• Work with scientists, engineers, and technical staff to apply skills to the challenge problem in computational science, numerical methods, mathematics, and science
• Gather and analyze data in support of scientific research
• Participate in research and challenge problem evaluation discussions
• Present results to scientists, engineers, and technical staff during final student briefing
• Actively participate in team meetings and large group meetings

Team leads will:

• Guide the research direction of 4–5 undergraduate students
• Provide advanced technical support to scientists, engineers, and technical staff in materials research and development
• Create and schedule meetings for your team
• Lead presentation of results to scientists, engineers, and technical staff during final student briefing
• Attend team lead meetings
• Students in a Master's program will be considered as a team lead with priority given to Ph.D. students

For more information, view the recording of our 2025 Data Science Challenge info session here.

What to include in your submission

1. Submit interest to the SmartRecruiters page
2. Statement of interest (1 page)
   • Please include:
     • Name and email address of the faculty member we should expect the letter of recommendation from. The application review committee will follow up with faculty on missing/late letters as necessary.
     • If you are interested in being a team lead, team member or if you're open to either.
     • Graduate students (or undergraduate students interested in being team leads): Include example(s) of your leadership and research experience in your statement of interest.
3. Resume, which should include any relevant coursework
4. A letter of recommendation by a faculty member (this person should be able to speak to the quality of your work and potentially as your role as a team member or team leader if you are interested in that position)
   • This is optional for undergraduates (unless applying to be a team lead then it is required) and is required for graduates.
   • Graduate students: The recommending faculty member should be your graduate advisor.
   • The letter of recommendation can be uploaded to the SmartRecruiters form OR it can be sent on your behalf to DataScienceChallenge [at] llnl.gov (DataScienceChallenge[at]llnl[dot]gov) (subject line: "Recommendation Letter <Your Last Name>")
     • Letters of recommendation are due by March 15.

Please note:

• This program is currently only open to UC Merced, UC Riverside and CSU Bakersfield at this time.
• Students who have graduated within one year of the Summer 2025 program are still eligible to submit their interest.