Projects and Mentors

example of random forest ensemble ML method

Guiding students as they tackle challenging problems is a lot of fun. Our students are incredibly talented and usually only need small hints to discover new ways of doing things that I didn’t anticipate.

—Dave Buttler, LLNL computer scientist and DSSI mentor

As a DSSI intern, you'll work on real projects with real data that represent the breadth and depth of data science research at LLNL. Our students tackle Challenge Problems that leverage large and varied datasets used in or generated from actual LLNL projects such as building networks from interaction data, large-scale data mining for predictive medicine, drug discovery using HPC simulations, video data summarization and classification, energy efficiency analysis using HPC, classification and forward modeling of hyper-spectral data, and much more. This curriculum helps students build technical experience and teamwork.

Our interns are also paired with mentors—experts across many data science fields at the Lab—whose projects align with students' skills and interests. Check out some of the recent Challenge Problems and mentors below.

2020 Challenge Problems

Mentor Spotlight

Jason Bernstein portrait

Jason Bernstein

After completing a PhD in Statistics at Penn State in 2016, Jason joined the Applied Statistics Group (ASG) at LLNL as a postdoc and is now a staff member in the group. He enjoys working with DSSI interns on research problems that are application driven and involve statistical computing, uncertainty quantification, and machine learning. For the first virtual DSSI program in 2020, Jason worked with a graduate student on applying reinforcement learning to spacecraft in stochastic environments. In 2018, Jason and fellow ASG member Katie Schmidt worked with a student on Bayesian calibration of material strength models using different data types. On the weekends, he enjoys exploring San Francisco and hiking around the Bay Area.


Ready for the next step?

Visit our applications page to read FAQ about the program, apply to the job posting, or contact us for more information.