LLNL will lend its expertise in vaccine research and computing resources to the Human Vaccines Project consortium to aid development of a universal coronavirus vaccine and improve understanding of immune response.
Computational biology is using HPC to rapidly design and develop ways to treat cancer and COVID. LLNL researcher Felice Lightstone discusses ATOM (Accelerated Therapeutic Opportunities in Medicine) in this edition of SC21 TV.
From studying radioactive isotope effects to better understanding cancer metastasis, the Laboratory’s relationship with cancer research endures some 60 years after it began, with historical precedent underpinning exciting new research areas.
Brian Gallagher works on applications of machine learning for a variety of science and national security questions. He’s also a group leader, student mentor, and the new director of LLNL’s Data Science Challenge.
On a recent video episode of The Data Standard Podcast, biostatistician Nisha Mulakken discusses the Lawrence Livermore Microbial Detection Array (LLMDA) system, which has detection capability for all variants of SARS-CoV-2.
The ADAPD program held a virtual meeting to highlight science-based, data-driven analysis work to advance AI innovation and AI-enabled systems to enhance the U.S. nuclear proliferation detection activities.
LLNL is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10.
Led by computational scientist Youngsoo Choi, the Data-Driven Physical Simulation reading group has been meeting biweekly since October 2019. The pandemic almost disbanded the group... until it turned into a virtual seminar series.
Coinciding with International Women’s Day on March 8, LLNL’s 4th Women in Data Science (WiDS) regional event brought women together to discuss successes, opportunities and challenges of being female in a mostly male field.