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Media Contacts
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Scientists at the U.S. Department of Energy’s Brookhaven National Laboratory have new experimental evidence and a predictive theory that solves a long-standing materials science mystery: why certain crystalline materials shrink when heated.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
A modern, healthy transportation system is vital to the nation’s economic security and the American standard of living. The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) is engaged in a broad portfolio of scientific research for improved mobility
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.
Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in
In Hong Wang’s world, nothing is beyond control. Before joining Oak Ridge National Laboratory as a senior distinguished researcher in transportation systems, he spent more than three decades studying the control of complex industrial systems in the United Kingdom.
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.