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Stony Brook University Researchers Chosen for Landmark DOE Genesis Mission AI-for-Science Awards
More than $2.4M will support collaborations with Brookhaven National Lab and other institutions to address complex science and technology challenges WASHINGTON, D.C., July 22, 2026 – Researchers at the State University of New York at Stony Brook (Stony Brook University) secured five inaugural awards through the U.S. Department of Energy’s (DOE) Genesis Mission, a national AI-for-science
Berkeley Lab to Lead 13 New Genesis Mission AI Projects
Researchers will apply AI, supercomputing, and advanced instruments to accelerate discoveries for energy, science, and national security.
DOE Unveils First Genesis Mission Awards for AI-Driven Science
Nearly 300 projects selected from historic RFA response spanning all 50 states to accelerate breakthroughs in energy, discovery science, and national security. WASHINGTON, July 22, 2026 — The U.S. Department of Energy (DOE) today announced the first projects selected under the Genesis Mission Request for Applications (RFA). The national portfolio of research teams will help develop […]
Department of Energy's New AI-for-Science ‘Genesis Mission’ Awards Funding to 5 UT Research Projects
Five UT teams have been awarded funding from the DOE’s Genesis Mission, an initiative working to harness artificial intelligence for advances in energy dominance, discovery science and national security.
Harnessing abundant electricity from the sun, and other CU Boulder science tapped for Genesis Mission
CU Boulder was awarded more than $2.1 million in grants for the U.S. Department of Energy's highly competitive Genesis Mission. The science behind the awards
Stony Brook University Researchers Chosen for Landmark DOE Genesis Mission AI-for-Science Awards
More than $2.4M will support collaborations with Brookhaven National Lab and other institutions to address complex science and technology challenges Researchers at the State University of New York at Stony Brook (Stony Brook University) secured five inaugural awards through the U.S. Department of Energy’s (DOE) Genesis Mission, a national AI-for-science initiative designed to accelerate scientific
Nvidia Commits $1B To US Science As CEO Jensen Huang Backs Trump’s Genesis Mission
Nvidia commitment will be dispersed over five years with the aim of advancing U.S. scientific research and computing capabilities.
The Genesis Mission: How AI Supercomputing Is About to Reshape American Science and Energy
DOE's Dr. Dario Gil explains how the Genesis Mission will use AI supercomputing to transform U.S. science, energy, and engineering.
New AI Inference Service Now Ready for Science at Argonne
AI can help accelerate scientific discovery, but setting up and running a foundation model is not a simple task. Thanks to the work of the Argonne Leadership Computing Facility, scientists affiliated with DOE National Labs and the Genesis Mission can now tap into a new AI inference service running on ALCF supercomputers. Dubbed the ALCF […]
Fermilab storage infrastructure enables AI-driven scientific and research discovery for DOE’s Genesis Mission
The U.S. Department of Energy’s Genesis Mission is building a new era of AI-driven scientific discovery — and it requires far more than powerful supercomputers to succeed. To support this national effort, Fermilab’s Fermi Data Platform is providing secure, large-scale data infrastructure needed to make advanced AI research possible across the American Science Cloud.
Anthropic Commits $150M To AI Science Mission
Anthropic is committing $150 million over three years to the federal government’s Genesis Mission, expanding access to its Claude AI models.
Inside Genesis Mission’s ‘All of Government’ Approach to AI for Science
There are now 20 different government agencies participating in the Department of Energy’s Genesis Mission project to advance science and engineering through AI. During the Genesis Mission Summit last week, representatives from the NIH, NASA, NSF, and Department of War discussed what they hope to get out of the project, and the contributions they hope […]
NYU Faculty Drive Three US Department of Energy Genesis Mission Projects to Accelerate AI-Driven Discovery
Faculty across Arts and Science, Courant, and Tandon will help develop AI tools for quantum computing, decentralized scientific reasoning, and automated hypothesis generation
Genesis Mission: why Trump’s plan to put AIs in charge of science could backfire
AI enthusiasts are right that projects like AlphaFold are a huge leap forward, but the philosophy of science shows why excluding humans undermines it.
Old Dominion University Selected for Two Federal Genesis Mission Awards Advancing Artificial Intelligence for Scientific Discovery
The next generation of scientific discovery will not come from artificial intelligence (AI) replacing scientists. It will come from AI helping them ask better questions, solve more complex problems and reach reliable answers faster.
A Pitt-led team plans to automate quantum computing research with a Department of Energy grant
Part of the Genesis Mission, a national effort to harness AI for scientific discovery, the project could enable new chemistry and materials science.
Genesis Mission: SYNAPS-I Brings Agentic AI to Experimental Workflows
With support from ALCF computing resources and AI services, the SYNAPS-I team demonstrated a new agentic AI platform that uses natural-language instructions to automate complex experimental workflows as part of the DOE Genesis Mission. Oct. 8, 2026 — Science has increasingly used artificial intelligence (AI) as a kind of microscope — sorting data, analyzing images […]
Powering America's Genesis Mission: Microsoft's commitment to scientific discovery
Today, we’re excited to share a long-term commitment to the Department of Energy’s (DOE) Genesis Mission, backed by a $60 million investment designed to accelerate AI for science and the breakthroughs it can deliver for the country. This deepened commitment includes Microsoft’s new Scientific Partnership Advancing Research & Knowledge coordination hub and program office, otherwise...
Harnessing Abundant Electricity From the Sun—and Other CU Boulder Science Tapped for Genesis Mission
Three CU Boulder-led projects and three collaborative projects selected through the U.S. Department of Energy's Genesis Mission. Research will advance artificial intelligence for fusion energy, quantum computing, particle physics and water prediction. Awards recognize CU Boulder's leadership in applying AI to some of the nation's most complex scientific challenges.
Emory receives U.S. Genesis Mission award to speed discovery through AI
Emory physicists will lead a team using AI to advance understanding of the fluid dynamics of plasma — from the lab to the cosmos — through the Department of Energy’s Genesis Mission.
White House Announces Over $6B in Science Initiatives
The White House has announced over $6 billion in science initiatives, including $2.4 billion for the Genesis Mission Consortium.
Trump’s $293 Million Bet to Supercharge Science Faces Spending Headwinds
US AI push faces funding tensions as DOE’s Genesis Mission competes with NSF cuts, raising concerns about long-term innovation, reports Yuqing Liu.
Trump spent 2025 attacking science. That could set back his “Genesis Mission.”
Trump’s AI “Manhattan Project” will fail if DOGE cuts are kept, critics say.
Nvidia is committing $1 billion to U.S. science over 5 years
The chipmaker announced the commitments Thursday at a Washington event tied to the Trump administration's Genesis Mission program
Michigan Tech Atmospheric Scientists Linked to Three Research Projects Selected for DOE Genesis Mission
Michigan Technological University researchers are involved in three proposals tapped by the U.S. Department of Energy for consideration under its recently launched Genesis Mission: Transforming Science and Energy with AI. The mission’s goal is to address national science and technology challenges using artificial intelligence.
SBU Researchers Chosen for DOE Genesis Mission AI Awards
Stony Brook University researchers secured five awards through the U.S. Department of Energy’s Genesis Mission, a national AI-for-science initiative.
New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Trump's Genesis Mission gets its first set of 26 sure-to-succeed objectives
: DoE bets AI can speed fusion, unlock decades of nuclear data, and probe fundamental physics
THE WEEK OF JULY 27, 2026
- White House releases vision for science - DOE expands Genesis Mission - Congress heads off on break
Fermilab to lead two new Genesis Mission awards to accelerate development of microelectronics and quantum
Two new awards will expand Fermilab’s critical role in the Genesis Mission by developing custom microelectronics and advancing quantum information science.
Texas A&M University joins the Genesis Mission to transform science using artificial intelligence
The U.S. Department of Energy announces projects in its unprecedented effort to use AI to accelerate science, harness new energy sources and bolster national security.
University of California partners with U.S. Department of Energy to advance energy, discovery and national security through Genesis Mission
UC scientists at seven campuses and three national labs lead 15 percent of DOE-funded projects.
DOE Genesis Mission awards will advance AI-driven science
Two Cornell-led research teams have been selected to receive nearly $1.2 million through Phase I of the U.S. Department of Energy’s Genesis Mission.
Trump admin to receive $100 million in compute credits for AI science initiative
The credits are intended to give Genesis Mission researchers access to computing power that smaller labs and companies struggle to secure as major AI firms lock up capacity.
Stanford and SLAC to lead Genesis Mission projects
The U.S. Department of Energy announced the first phase of funding for projects using artificial intelligence to tackle the nation’s most complex science and technology challenges, including six led by Stanford and SLAC National Accelerator Laboratory.
Scientists Release Biggest 2D Map of the Universe
Key Takeaways The DESI Legacy Imaging Surveys combined more than 263,000 telescope exposures to make the largest 2D map of the universe in visible and near-infrared light. Astronomers can pair the Legacy Surveys map with their own observations to explore our universe and search for rare phenomena. The 2D map serves as the foundation for the Dark Energy Spectroscopic Instrument survey to measure the universe in 3D and investigate dark energy. Hold on to your telescopes: the DESI Legacy Imaging Surveys team has released the largest-ever 2D color map of the universe. The 5.6-trillion-pixel map contains nearly 4 billion celestial objects, primarily stars and galaxies. The data is available for all to use and publicly viewable through the Legacy Survey Sky Viewer. Astronomers and citizen scientists can explore the map or combine it with their own observations to better understand our universe. Researchers can search for rare phenomena like gravitational lenses, observe fleeting events like supernovae, and investigate two of physics’ biggest mysteries: dark matter, the invisible substance that accounts for most of the mass in our universe, and dark energy, the force driving our universe’s accelerating expansion. The new map builds on earlier versions from the DESI Legacy Imaging Surveys that have already proved invaluable. To date, more than 1,800 science papers that reference the Legacy Surveys data have been published. “It’s part of the fabric of astronomy research now,” said David Schlegel, a co-lead of the Legacy Surveys and scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab). “When you’re working with astronomical objects today, you often start by pulling up the Legacy Imaging Viewer to see what you’re looking at.” Covering roughly 75% of the sky in visible and near-infrared light, the updated map provides a deep view of the extragalactic universe not blocked by the dust and stars of our own Milky Way. Researchers expect it will remain the most comprehensive 2D map of our universe for years to come. More than 160 scientists contributed to data collection for the project, and a team of 20 produced the final dataset released today. It was built by combining 263,407 telescope exposures from three ground-based sky surveys: the Dark Energy Camera Legacy Survey (DECaLS) at NSF Cerro Tololo Inter-American Observatory, the Mayall z-band Legacy Survey (MzLS) at NSF Kitt Peak National Observatory, and the Beijing-Arizona Sky Survey (BASS) at the University of Arizona’s Steward Observatory. That was supplemented by years of data from NASA’s Wide-field Infrared Survey Explorer (WISE) satellite mission and additional public data. “For our team, these data are fundamental to our investigation of the expansion history of the universe and the formation of our galaxy,” said Arjun Dey, co-lead of the Legacy Surveys and an astronomer at NSF NOIRLab. “But the skies belong to everyone, and this survey gives everyone the chance to explore the sky and marvel at its wonders.” Here be galaxies The DESI Legacy Imaging Surveys were originally conducted to prepare for the Dark Energy Spectroscopic Instrument (DESI) survey. The Legacy Surveys’ 2D map is essentially a deep photograph of the sky; it records where galaxies and stars appear and how bright they appear. This crucial step enables DESI to select objects and measure their light in different wavelengths to determine their distances, building the largest high-resolution 3D map ever made. Scientists study the way galaxies have clustered at different ages of the universe to track dark energy over time. In April 2026, DESI completed its original five-year survey ahead of schedule and with vastly more objects than expected. The early results have shown surprising hints that dark energy’s impact may be weakening over time — a paradigm shift that could potentially shape the predicted fate of our universe. DESI expects to publish improved results using their first five years of data in 2027 and is continuing observations into 2028. DESI was so efficient at observing galaxies, the Legacy Surveys map needed to expand. Early on, “it became clear we might run out of galaxies to look at and run out of sky, and we better start doing something about that,” said Schlegel, who also works on DESI. The new Legacy Surveys map has been used to select DESI targets since June 2026 and will guide the telescope’s operations over the coming years. Computing the cosmos Merging hundreds of thousands of images taken on 2,285 nights, each with unique atmospheric and telescope conditions, was a massive computational effort. It took about a year to develop the computer code and eight weeks to process all the images at the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab. Beyond supporting DESI, the Legacy Surveys will be a foundational reference for the next generation of telescopes. As new observatories like the NSF-DOE Vera C. Rubin Observatory (jointly funded by NSF and DOE’s Office of Science) and NASA’s Nancy Grace Roman Space Telescope come online, researchers can compare their observations with one of the deepest and most comprehensive views of the sky ever assembled. The Legacy Surveys data will also help scientists train artificial intelligence tools to analyze petabytes of astronomical data and accelerate new discoveries. It will be among the datasets used in an astrophysics pilot project within the American Science Cloud, part of the DOE’s Genesis Mission. The DESI Legacy Imaging Surveys are supported by the U.S. Department of Energy’s Office of High Energy Physics; the National Energy Research Scientific Computing Center, a DOE Office of Science user facility; the U.S. National Science Foundation, Division of Astronomical Sciences; and the partner institutions. DESI is supported by the DOE Office of Science and NERSC. Additional support for DESI is provided by the NSF; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the Secretariat of Science, Humanities, Technology and Innovation (SECIHTI) of Mexico; the Ministry of Science and Innovation of Spain; and by the DESI member institutions. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
THE WEEK OF DEC 8, 2025
- NDAA text released - S&T nominees face vote - Genesis Mission to get hearing
Trump admin to get $100M in compute credits for AI science initiative
The credits are intended to give Genesis Mission researchers access to computing power that smaller labs and companies struggle to secure.
How the Genesis Mission’s American Science Cloud Advances Innovation
Inder Monga Q&A on how Berkeley Lab experts are contributing to key aspects of DOE’s American Science Cloud project to accelerate science.
5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding
The projects, spanning fusion to critical minerals, are among 278 funded awards to national labs, companies, universities and non-profits in order to accelerate breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments.
Nvidia commits $1 billion to U.S. science and quantum computing
The chipmaker announced the commitments Thursday at a Washington event tied to the Trump administration's Genesis Mission program
Department of War Partners With the Genesis Mission to Proliferate AI
Led by the White House, the War Department is committing substantial resources and technical expertise to the success of the Genesis Mission, a national effort to leverage artificial intelligence to
White House Announces $6B Science Push, Including $2.4B Genesis Mission AI Commitments
White House Announces $6B Science Push, Including $2.4B Genesis Mission AI Commitments - CDO Magazine
Stony Brook University Researchers Chosen for DOE Genesis Mission AI-for-Science Awards
July 27, 2026 — Researchers at the State University of New York at Stony Brook (Stony Brook University) secured five inaugural awards through the U.S. Department of Energy’s (DOE) Genesis Mission, a national AI-for-science initiative designed to accelerate scientific discovery and strengthen U.S. leadership in innovation, energy and national security. The awards reinforce Stony Brook University’s […]
PNNL Researchers to Speak About Genesis Mission at National Science Bowl
Pacific Northwest National Laboratory’s Robert Rallo and Nathan Hodas speak to students about the future of AI RICHLAND, Wash., May 1, 2026 — Student winners of this year’s regional National Science Bowl competitions will hear about the future of AI from two researchers from the Department of Energy’s Pacific Northwest National Laboratory this spring. The […]
UMaine-led team selected for inaugural DOE Genesis Mission to advance AI in underground science
Beneath Maine’s salt marshes, an invisible transformation is constantly underway. Water moves through soil and rock. Chemicals react. Tiny microbes living underground help determine whether minerals dissolve or form, how fluids move and whether pollutants break down or spread. Existing computer models used to guide decisions about energy infrastructure and…
2025 in Review: ORNL’s Top Science News Stories
The Department of Energy’s Oak Ridge National Laboratory marked another year of research driven by innovation and collaboration in 2025, as reflected in the laboratory’s most-read stories. The year’s top story announced two new AI supercomputers, establishing ORNL’s vital role as part of DOE’s Genesis Mission, a national initiative to accelerate science through artificial intelligence.
DOE Announces $293 Million Genesis Mission Funding for Quantum Science and AI-Driven Research
DOE announces $293M Genesis Mission funding for AI-driven research in quantum information science, advanced manufacturing, biotechnology, and nuclear energy.
Argonne receives DOE funding to advance AI for science
Argonne receives funding from DOE’s Genesis Mission to conduct transformative AI research that will push the boundaries of energy, biology, materials science and more.