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A new paper in Nature Reviews Physics highlights growing adoption of autonomous data collection across multiple science areas.
Teaching machine learning the basics of accelerator physics is particularly useful in situations where actual data don’t exist.
A radar meteorologist drawn to convective clouds has a knack for open-source programming and the gift of gab.
Scientists developed an automated approach for experiments to intelligently explore complex scientific problems, with minimal human intervention.
Argonne scientists has leveraged artificial intelligence to train computers to keep up with the massive amounts of X-ray data taken at the APS.
The Department of Energy Computational Science Graduate Fellowship celebrates 30 years of cultivating leaders and innovators.
The new system will help users throughout the sciences get the most out of high-power lasers.
Simulations using the OLCF supercomputer could lead to better, faster turbines for jet engines and more.
Argonne-driven technology is part of an initiative to answer questions about the birth of matter & the building blocks that hold the universe together
The U.S. Department of Energy (DOE) announced $7.7 million in funding for 11 studies to improve understanding of Earth system predictability and DOE’s Energy Exascale Earth System Model (E3SM), a state-of-the-science climate model.