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Media Contacts
A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL.
In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
As a data scientist, Daniel Adams uses storytelling to parse through a large amount of information to determine which elements are most important, paring down the data to result in the most efficient and accurate data set possible.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
Despite strong regulations and robust international safeguards, authorities routinely interdict nuclear materials outside of regulatory control. Researchers at ORNL are exploring a new method that would give authorities the ability to analyze intercepted nuclear material and determine where it originated.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
Anuj J. Kapadia, who leads the Advanced Computing in Health Sciences Section at the Department of Energy’s Oak Ridge National Laboratory, was named a 2024 Fellow by the American Association of Physicists in Medicine.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.