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The U.S. National Science Foundation is investing $6.2 million in 24 exceptional researchers who have been selected as NSF Established Program to Stimulate Competitive Research (EPSCoR) Research Fellows. This prestigious program aims to support early- and mid-career scientists in states that receive lower levels of NSF funding, helping them to establish a strong foundation for or relaunch their research careers.

The EPSCoR Research Fellows (ERF) program offers numerous benefits to fellows, including financial support, mentorship opportunities and access to cutting-edge research facilities. The fellows will receive funding and support from NSF to pursue their research projects and establish strong collaborations at national research facilities. ERF also supports fellows in establishing themselves as leaders in their fields and making valuable contributions to the scientific community.

“EPSCoR is a national program that ensures our federal research dollars reach every corner of our nation, and that the Americans who live in these 25 states and territories have the same opportunities to be part of the STEM workforce, access to world-class facilities and partnerships- all of which unlock breakthroughs that wouldn’t happen otherwise.” said Brian Stone, performing the duties of the NSF director. “By funding Research Fellows, the American taxpayers are directly investing in the next generation of discoveries that create jobs, strengthen local economies, and expand America’s innovation capacity.”

The 24 researchers selected as EPSCoR Research Fellows represent

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The U.S. National Science Foundation National Quantum Virtual Laboratory (NSF NQVL) is coming into sharper focus with the selection of the first four teams that will design high-tech infrastructure to be broadly used across the country. NSF is investing $16 million in the four teams, with each receiving $4 million over two years. The NSF NQVL initiative is an ambitious effort to accelerate the development of useful quantum technologies by providing researchers anywhere in the U.S. with access to specialized resources.

The teams selected by NSF will design practical ways to expand access to the hardware and software needed for quantum science, engineering and technology development, which are currently highly bespoke and concentrated in relatively few labs. Among the design projects are plans to create shareable, networked quantum computers that can be used for experimentation from any location and a “digital twin” (a dynamic simulation that changes and responds to inputs) of a quantum computer that can be used by any U.S. researcher to test and refine new quantum algorithms.

“The National Quantum Virtual Laboratory is a critical bridge between basic discovery and deployment, specifically focused on turning America’s leadership in fundamental quantum science into practical technologies, products, and systems that will strengthen our nation’s competitiveness and ensure U.S. dominance in this field for decades to come,” said Brian Stone, performing the duties of

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The U.S. National Science Foundation today announced a new solicitation to establish a National Artificial Intelligence Research Resource Operations Center (NAIRR-OC). This marks a critical, initial step in transitioning the National AI Research Resource (NAIRR) from a successful pilot to laying the foundations for a sustainable, coordinated national program that will advance U.S. research capabilities and global leadership in AI.

Many researchers and educators lack the critical AI tools and resources to investigate fundamental AI questions and train students.

Launched in 2024, through a novel public-private partnership construct, the NAIRR Pilot aims to build a national infrastructure that expands access to the computational, data, model, and training resources needed to drive AI innovation and train the next generation.

Backed by the support of 14 federal agencies and 28 private-sector and nonprofit partners, the NAIRR Pilot has already connected over 400 U.S. research teams with computing platforms, datasets, software, and models — accelerating breakthroughs in fields from agriculture and drug discovery to cybersecurity and education.

The establishment of NAIRR-OC is a strategic, forward-looking investment in the nation’s scientific enterprise. It directly supports the White House’s AI Action Plan, which emphasizes the need for sustained operational capabilities for the NAIRR and broader access to AI resources for the research community.

“The NAIRR Operating Center solicitation marks a key step in the transition from the NAIRR Pilot to building a

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The U.S. National Science Foundation today announced two major advancements in America’s AI infrastructure: the launch of the Integrated Data Systems and Services (NSF IDSS) program to build out national-scale data systems and the selection of 10 datasets for integration into the National Artificial Intelligence Research Resource (NAIRR) Pilot.

These efforts directly align with priorities outlined in the White House AI Action Plan, which calls for investments in research infrastructure and datasets to strengthen U.S. leadership in AI research, education and innovation.

NSF IDSS: Building a national integrated data infrastructure

The NSF IDSS program will fund the development and operation of powerful national-scale systems and associated services that allow researchers across the country to access, use and share scientific data — accelerating innovation and strengthening American competitiveness in AI and other sectors.

Currently, there are no dedicated programs at NSF that support operational national-scale data systems. IDSS fills this gap by enabling the deployment of high-impact platforms that serve research and education communities and interoperate with other federal science and data infrastructure efforts.

A robust data infrastructure is also critical to the success of the NSF-led NAIRR Pilot, a key initiative expanding access to AI research resources. As AI transforms sectors from health care and agriculture to energy and national defense, researchers face the challenge of accessing and integrating vast data to power advanced AI systems. Awarded

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