UC Merced joins LLNL for a Data Science Challenge

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Suzanne Sindi, UC Merced | 209.228.4224

Brian Gallagher, LLNL | 925.424.4468

Jennifer Bellig, LLNL admin | 925.699.1514

You could help advance world-class science this summer!

We’re building multidisciplinary teams to tackle real-world data science challenges. And we need 20 of UC Merced’s finest scholars to make it happen.

Apply by March 13, 2022 (midnight PST): llnl-data-science-challenge [at] llnl.gov

Your application must include:

  • Statement of interest (1 page)
  • Resume
  • 1 letter of recommendation by a UC Merced faculty member sent on your behalf to the email address above (subject line: "Recommendation Letter <Your Last Name>")
    • Please include in your statement of interest the name and email address of the faculty member we should expect the letter from. The application review committee will follow up with faculty on missing/late letters as necessary.
  • Graduate students: Include example(s) of your leadership and research experience in your statement of interest. The recommending faculty member should be your advisor.
  • Send all application materials to the email address listed above.

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. This intensive 2-week full-time training program provides challenging exercises and assignments, virtual 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. Read about the 2021 UCM Challenge.

You’ll solve an exciting problem in drug discovery for COVID-19. Traditional drug discovery involves many time-consuming and expensive experimental steps. Machine learning and other data science techniques can drastically accelerate this process, which is especially important in a global pandemic.

In this challenge, you will work with a massive database of virtual molecule screening results, chemical and protein structures, and designed synthetic antibodies to identify drug compounds that can be used to create medicines that prevent and treat COVID-19 infections. Read about your LLNL mentors.

A stipend will be provided.

Undergraduate students will:

  • Work with scientists, engineers, and technical staff to support to LLNL projects
  • Participate in a real-world drug discovery data problem
  • 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

Graduate students will:

  • Serve as team lead, guiding the research direction for 4 undergraduate students
  • Provide advanced technical support to LLNL scientists, engineers, and technical staff
  • Demonstrate work via presentations

Please note, students will participate in person at UC Merced as long as COVID restrictions allow. If necessary, this will be a virtual program.