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

Brenden Petersen

Brenden Petersen

Brenden Petersen isn’t content merely applying advanced data science methods to real-world problems. He’d rather tackle challenges where, he says, “the state-of-the-art doesn’t cut it.” Since joining LLNL’s Computational Engineering Division in 2016, he pursues deep reinforcement learning (RL) solutions for many fields including cybersecurity, energy, and healthcare. Whereas deep learning traditionally addresses prediction problems, RL solves control problems. He explains, “RL provides a framework for learning how to behave in a task-completion scenario. Working in the field feels very goal-oriented, even competitive. Each application is a new personal challenge.” Brenden earned his biomedical engineering PhD through a joint program at UC Berkeley and UC San Francisco.

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.