CACTUS provides AI-powered cheminformatics for autonomous science.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Summer internship programs with partnering colleges provide pathways for students to explore careers in science, technology, engineering, and math.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

HiSVSIM enables large-scale quantum simulations through graph partitioning.