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.

PMedIC, the PNNL and OHSU joint research collaboration, contributes to student success and impact in biomedicine.

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.

PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.

Data reveals mechanisms in our bodies that can help us fight viral pathogenesis.

New apps help researchers with statistical analyses of data.

PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

An initiative from Washington State University and Snohomish County leaders is aiming to make Paine Field a nexus for testing and improving sustainable aviation fuels made from non-petroleum materials.

Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

Ripples demonstration will take place at the DOE booth at the International Conference for High Performance Computing, Networking, Storage, and Analysis.

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.

PNNL’s Richard Saldanha will lead a new project to benchmark and validate models of cosmic ray exposure