Topic: Students

Every year, LLNL welcomes hundreds of interns for an experiential, hands-on approach to learning. Working with some of the brightest minds in their fields, our interns have the opportunity to explore new projects, build their skills, connect with mentors, and integrate into Lab culture.

This season’s hackathon featured Lab improvement projects, work tasks, and personal enrichment.

The event brought together 35 University of California students—ranging from undergraduates to graduate-level students from a diversity of majors—to work in groups to solve four key tasks, using actual electrocardiogram data to predict heart health.

Since 2018, the Lab has seen tremendous growth in its data science community and has invested heavily in related research. Five years later, the Data Science Institute has found its stride.

LLNL's popular lecture series, “Science on Saturday,” runs February 4–25. The February 18 lecture is titled "Supersizing Computing: 70 Years of HPC."

Discovery Center reopens to visitors on Feb. 1, after nearly three years of closure due to COVID-19, featuring renovations and new exhibits.

After 10 years and 33 hackathons, nothing can stop this beloved tradition.

For the first time in the DSC series since the COVID-19 pandemic began in 2020, Lab mentors visited the college campus to provide in-person guidance for five teams of UC Merced students.

With a history of student participation and committee service, LLNL computer scientist Kathleen Shoga chaired this year’s competition.

Computing’s newest internship program focuses on DevOps methodologies. The inaugural class of 2021 built a persistent data services provisioning application that will soon assist real Livermore Computing users.

CASC and the Data Science Institute welcomed a new academic partner to the 2021 Data Science Challenge program: the University of California Riverside campus.

Each new season brings another hackathon, and Computing’s 2021 summer event took place on August 12–13.

LLNL and Purdue are partnering to speed up drug design using computational tools under the Accelerating Therapeutic Opportunities in Medicine project.

UC Merced students engaged with LLNL mentors and peers to address a challenge problem, using machine learning to identify potentially hazardous asteroids that could pose a threat to humanity.