Armed with some of the world’s most advanced instrumentation, researchers at PNNL are working to analyze huge amounts of data and uncover hidden biological connections.
For PNNL’s Jonathan Evarts, Hope Lackey, and Erik Reinhart, this partnership with WSU opened doors and provided opportunities for their scientific careers to flourish.
Staff at PNNL recently traveled to Cyprus to facilitate a multilateral workshop on chemical forensics investigations hosted by the U.S. Department of State, Office of Weapons of Mass Destruction Terrorism.
Staff at PNNL recently visited the University of Texas at San Antonio to deliver lectures on international law, arms control, and nuclear nonproliferation during Nuclear Policy Week.
PNNL staff scientist selected as a guest editor for a special issue titled “Ligand-Metal Complementarity in Rare Earth and Actinide Chemistry,” in the well-known journal Inorganic Chemistry.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
PNNL has joined Gender Champions in Nuclear Policy, a leadership network that brings together leaders of organizations working in nuclear policy who are committed to breaking down gender barriers.
Germany Harris, Dewayne Maye, Sarah Olocha, Shaniya Pettway, and Rayonna Redmon became the first interns of the Minority Serving Institution Partnership Program Partnership for Radiation Studies Consortium at PNNL.
PNNL Biomedical Scientist Geremy Clair has taken on new roles as an editor for two journals; Frontiers In Cellular And Infection Microbiology and Frontiers In Molecular Biosciences.
Researchers at PNNL leveraged their experiences to connect with attendees at the 2022 SACNAS National Diversity in STEM Conference, October 27–29, 2022, in San Juan, Puerto Rico.
New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.