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

Bradley Crowell with the U.S. Nuclear Regulatory Commission sees advanced materials integrity, radiological measurement, and environmental capabilities on his first visit to PNNL.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

Joint appointments at PNNL and UTEP are teaming together to strengthen and protect sensitive data.

The Forefront23 workshop convened researchers, scientists, and engineers who are just that: at the forefront of cybersecurity and nuclear nonproliferation.

Workers feeling a specific form of stress are more likely than others to become the victims of a phishing attack, according to a new study.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

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

PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Based on the early success of CHIRP and the urgency to build the future cybersecurity workforce, the program recently received five million dollars in funding through the FY23 Defense Appropriations Bill, via SSC.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Deep learning helps make predictions on the effects of the El Niño-Southern Oscillation on river flows more accurate.

PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.