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Media Contacts
Hilda Klasky, an R&D staff member in the Scalable Biomedical Modeling group at ORNL, has been selected as a senior member of the Association of Computing Machinery, or ACM.
The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.
Mirko Musa spent his childhood zigzagging his bike along the Po River. The Po, Italy’s longest river, cuts through a lush valley of grain and vegetable fields, which look like a green and gold ocean spreading out from the river’s banks.
When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.
Scientists at ORNL have confirmed that bacteria-killing viruses called bacteriophages deploy a sneaky tactic when targeting their hosts: They use a standard genetic code when invading bacteria, then switch to an alternate code at later stages of
Three scientists from the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Association for the Advancement of Science, or AAAS.
Seven scientists at the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors, in recognition of their obtaining 14 or more patents during their careers at the lab.
Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.