RSS feed source: National Science Foundation

Synopsis

Correctness for Scientific Computing Systems (CS2) is a joint program of the National Science Foundation (NSF) and the Department of Energy (DOE). The program addresses challenges that are both core to DOE’s mission and essential to NSF’s mission of ensuring broad scientific progress. The program’s overarching goal is to elevate correctness as a fundamental requirement for scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows.

At an elementary level, correctness of a system means that desired behavioral properties will be satisfied during the system’s execution. In the context of scientific computing, correctness can be understood, at both the level of software and hardware, as absence of faulty behaviors such as excessive numerical rounding, floating-point exceptions, data races deadlocks, memory faults, violations of specifications at interfaces of system modules, and so on. The CS2 program puts

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RSS feed source: National Science Foundation

Synopsis

Plasma science is a transdisciplinary field of research where fundamental studies in many disciplines, including plasma physics, plasma chemistry, materials science, and space science, come together to advance knowledge for discovery and technological innovation.  The primary goal of the ECosystem for Leading Innovation in Plasma Science and Engineering (ECLIPSE) program is to identify and capitalize on opportunities for bringing fundamental plasma science investigations to bear on problems of societal and technological need within the scope of science and engineering supported by the participating NSF programs.

The ECLIPSE meta-program has been created to foster an inclusive community of scientists and engineers, an ecosystem spanning multiple NSF Directorates, in the pursuit of translational research at the interface of fundamental plasma science and technological innovation.  The ECLIPSE program builds on the long history of NSF leadership in supporting multi-disciplinary research in plasma science and engineering, and is intended to enhance organizational

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RSS feed source: National Science Foundation

Synopsis

The Established Program to Stimulate Competitive Research (EPSCoR) supports the mission of the U.S. National Science Foundation (NSF) by promoting nationwide scientific progress. Through this program, NSF fosters partnerships among academic institutions, government entities, industry, and non-profits. These collaborations aim to drive long-term improvements in research infrastructure, enhance R&D capacity, and boost the research competitiveness of eligible EPSCoR jurisdictions, including states, territories, and commonwealths. 

A jurisdiction’s research ecosystem is the interconnected network of institutions, organizations, researchers, trainees, community stakeholders, and resources that contribute to the process of research and innovation that advances fundamental knowledge, generates use-inspired products, and ultimately cultivates beneficial societal impacts for a jurisdiction. E-RISE supports hypothesis-driven or problem-driven research and fosters the development of research teams and products in a scientific topical area that aligns with a jurisdiction’s research ecosystem and priorities, as detailed in the jurisdiction’s Science and Technology

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RSS feed source: National Science Foundation

Synopsis

Science of Learning and Augmented Intelligence (SL) supports potentially transformative research that develops basic theoretical insights and fundamental knowledge about principles, processes and mechanisms of learning, and about augmented intelligence — how human cognitive function can be augmented through interactions with others or with technology, or through variations in context. 

The program supports research addressing learning in individuals and in groups, across a wide range of domains at one or more levels of analysis, including molecular and cellular mechanisms; brain systems; cognitive, affective and behavioral processes; and social and cultural influences. 

The program also supports research on augmented intelligence that clearly articulates principled ways in which human approaches to learning and related processes, such as in design, complex decision-making and problem-solving, can be improved through interactions with others or through the use of artificial intelligence in technology. These could include ways of using knowledge

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