OARS funding Computer

Major goals of NSF's D-ISN include: Improve understanding of the operations of illicit supply networks and strengthen the ability to detect, disrupt, and dismantle them. Enhance research communities that effectively integrate operational, computational, social, cultural and economic expertise to provide methods and strategies to combat this complex and elusive global security challenge. Catalyze game-changing technological innovations that can improve discovery and traceability of illicitly sourced products and illicitly sourced labor inputs to products. Provide research outcomes that inform U.S. national security, law enforcement and economic development needs and policies.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in making research data and artificial intelligence (AI) models findable, accessible, interoperable, and reusable (FAIR1) to facilitate the development of new AI applications in SC's congressionally authorized mission space, which includes the advancement of AI research and development. In particular, ASCR is interested in supporting FAIR benchmark data for AI; and FAIR frameworks for relating data and AI models. For this FOA, AI is inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP). Data, in this context, are the digital artifacts used to generate AI models and/or employed in combination with AI models during inference. An AI model is an inference method that can be used to perform a "task," such as prediction, diagnosis, or classification. The model is developed using training data or other knowledge. An AI task is the inference activity performed by an artificially intelligent system.

The purpose of this Funding Opportunity Announcement (FOA) is to stimulate translation of scientific discoveries and engineering developments in imaging, data science and/or spectroscopic technologies into methods or tools that address contemporary problems in understanding the fundamental biology, potential risk of development, diagnosis, treatment, and/or disease status for cancer or other disease.

The International Research and education Network Connections (IRNC) Base program supports high-performance network connectivity required by international science and engineering research and education collaborations involving the NSF research community. High-performance network connections and infrastructure funded by this program are intended to support science and engineering research and education applications, and preference will be given to solutions that provide the best economy of scale and demonstrate the ability to support the largest communities of interest with the broadest services. Funded projects will assist the U.S. research and education community by enabling state-of-the-art international network services and access to increased collaboration and data services. NSF expects to make 3 to 10 awards in production R&E network infrastructure; 1 to 3 awards in international testbeds; and 1 award in Engagement.

The National Science Foundation (NSF) supports fundamental research and education in science and engineering. NSF's role results in new knowledge and tools as well as a capable, innovative workforce. These complementary building blocks of innovation have led to revolutionary technological advances and wholly new industries. NSF seeks to further develop and nurture a national innovation ecosystem built upon fundamental research that guides the output of scientific and engineering discoveries closer to the development of technologies, products, and services that benefit society. The goal of the NSF Innovation Corps (I-Corps) Program is to use experiential education to help entrepreneurial researchers reduce the time necessary to translate a promising idea from the laboratory bench to widespread implementation. In addition to accelerating technology translation, NSF seeks to reduce the risk associated with technology development conducted without insight into industry requirements and challenges.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The far-reaching impact and rate of innovation in the computer and information science and engineering fields has been remarkable, generating economic prosperity and enhancing the quality of life for people throughout the world. More than a decade ago, the National Science Foundation's (NSF) Directorate for Computer and Information Science and Engineering (CISE) established the Expeditions in Computing (Expeditions) program to build on past successes and provide the CISE research and education community with the opportunity to pursue ambitious, fundamental research agendas that promise to define the future of computing and information.

The far-reaching impact and rate of innovation in the computer and information science and engineering fields has been remarkable, generating economic prosperity and enhancing the quality of life for people throughout the world. More than a decade ago, the National Science Foundation's (NSF) Directorate for Computer and Information Science and Engineering (CISE) established the Expeditions in Computing (Expeditions) program to build on past successes and provide the CISE research and education community with the opportunity to pursue ambitious, fundamental research agendas that promise to define the future of computing and information. In planning Expeditions projects, investigators are strongly encouraged to come together within or across departments or institutions to combine their creative talents in the identification of compelling, transformative research agendas that look ahead by at least a decade and promise disruptive innovations in computer and information science and engineering for many years to come.

The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation's most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Activities pursued by early-career faculty should build a firm foundation for a lifetime of leadership in integrating education and research. NSF encourages submission of CAREER proposals from early-career faculty at all CAREER-eligible organizations and especially encourages women, members of underrepresented minority groups, and persons with disabilities to apply.

The DOE SC program in Biological and Environmental Research (BER), hereby announces its interest in receiving applications for research in developing computational approaches that can integrate large, disparate data types from multiple and heterogeneous sources, such as those used in the Genomic Science program (GSP) (http://genomicscience.energy.gov). Research supported by awards resulting from this FOA will promote human understanding of the natural world through analysis of high-throughput biological systems data. BER has an ongoing mission of improving translation from the molecular to cellular realm within scientific disciplines supported by DOE.

The program supports four main research themes that are envisioned to advance the goal of ubiquitous co-robots:scalability,customizability,lowering barriers to entry, andsocietal impact,includinghuman safety. Topics addressingscalabilityinclude how robots can collaborate effectively with orders of magnitude more humans or other robots than is handled by the current state of the art; how robots can perceive, plan, act, and learn in uncertain, real-world environments, especially in a distributed fashion; and how to facilitate large-scale, safe, robust and reliable operation of robots in complex environments.Customizabilityincludes how to enable co-robots to adapt to specific different tasks, environments, or people, with minimal modification to hardware and software; how robots can personalize their interactions with people; and how robots can communicate naturally with humans, both verbally and non-verbally. Topics inlowering barriers to entryshould focus on lowering the barriers for conducting fundamental roboticsresearchand research on integrated robotics application. This may include development of open-source co-robot hardware and software, as well as widely-accessible testbeds. Outreach or using robots in educational programs do not, by themselves, lower the barriers to entry for robotics research. Topics insocietal impactinclude fundamental research to establish and infuse robotics into educational curricula, advance the robotics workforce through education pathways, and explore the social, economic, ethical, security, and legal implications of our future with ubiquitous collaborative robots.

The Nation's advanced research cyberinfrastructure (CI) ecosystem catalyzes discovery and innovation across all areas of science and engineering (S&E) research and education. The increasingly complex and rapidly evolving S&E landscape requires an agile, integrated, robust, trustworthy, and sustainable CI ecosystem that will drive new thinking and transformative discoveries in all areas of research and education. The success of this vision depends on the ability of the research community to be able to easily and effectively access and use state-of-the-art research CI resources and services in a timely way. This, in turn, drives a set of requirements on the development, operation, and evolution of the CI ecosystem. First, research CI resources and services must be designed to leverage and drive innovations, and they must be user-centric and interoperable to enable the efficient, flexible end-to-end discovery pathways that are increasingly essential for the conduct of research. Second, the information, expertise, and services needed to maximally utilize the CI ecosystem must be disseminated broadly and concertedly to the research community. The NSF Cyberinfrastructure Centers of Excellence (CI CoE) Program aims to realize the above vision by supporting hubs of expertise and innovation targeting specific areas, aspects, or stakeholder communities of the research CI ecosystem.

Through its Fellowship Programs, the Ford Foundation seeks to increase the diversity of the nation's college and university faculties by increasing their ethnic and racial diversity, maximize the educational benefits of diversity, and increase the number of professors who can and will use diversity as a resource for enriching the education of all students.

The purpose of this Notice of Funding Opportunity (NOFO) is to support innovative research to develop and apply computational tools and mathematical methods for: 1) modeling the spread of pathogens that cause healthcare-associated infections (HAIs) and related antimicrobial resistant (AR) infections; 2) predicting outbreaks of HAI pathogens and trends in the burden of antimicrobial resistant and susceptible HAIs; and 3) investigating the effectiveness of intervention strategies. The models should be developed with the intent that they will be tools for researchers, policymakers, or public health workers who want to better understand and respond to HAIs in the United States. This NOFO will also create a network of leaders in the fields of HAI and AR modeling that will be a resource for informing the development of relevant evidence-based policy. MInD-Healthcare will provide a network of leading modelers to respond to evolving public health needs and emergencies in healthcare settings.

Science-driven requirements are the primary motivation for any proposed activity. Proposals will be evaluated on the strength of the science enabled (including research and education) as drivers for investment and innovation in data networking infrastructure, innovation and engineering. A common theme across all aspects of the CC* program is the critical importance of the partnership among campus-level CI experts, including the campus Information Technology (IT)/networking/data organization, contributing domain scientists, research groups, and educators necessary to engage in, and drive, new networking capabilities and approaches in support of scientific discovery. Proposals across the program should reflect and demonstrate this partnership on campus. Proposals will be evaluated on the strength of institutional partnerships, as they are expected to play a central role in developing and implementing the eventual network and data infrastructure upgrades.

The Campus Cyberinfrastructure (CC*) program invests in coordinated campus-level networking and cyberinfrastructure improvements, innovation, integration, and engineering for science applications and distributed research projects. Learning and workforce development (LWD) in cyberinfrastructure is explicitly addressed in the program. Science-driven requirements are the primary motivation for any proposed activity.

The Division of Molecular and Cellular Biosciences (MCB) has developed a new opportunity to enable researchers with a strong track record of prior accomplishment to pursue a new avenue of research or inquiry. This funding mechanism is designed to facilitate and promote a PI's ability to effective adopt empowering technologies that might not be readily accessible in the PI's current research environment or collaboration network. Transformative research likely spans disciplines and minimizing the practical barriers to doing so will strengthen research programs poised to make significant contributions. The award is intended to allow mid-career or later-stage researchers (Associate or Full Professor, or equivalent) to expand or make a transition in their research programs via a sabbatical leave or similar mechanism of professional development and then develop that research program in their own lab. This award will also enable the PI to acquire new scientific or technical expertise, facilitate the investigator's competitiveness, and potentially lead to transformational impacts in molecular and cellular bioscience.

Generating Electricity Managed by Intelligent Nuclear Assets(GEMINA) Agency Overview: The Advanced Research Projects Agency - Energy (ARPA-E), an organization within the Department of Energy (DOE), is chartered by Congress in the America COMPETES Act of 2007 (P.L. 110-69), as amended by the America COMPETES Reauthorization Act of 2010 (P.L. 111-358) to: "(A) to enhance the economic and energy security of the United States through the development of energy technologies that result in- (i) reductions of imports of energy from foreign sources; (ii) reductions of energy-related emissions, including greenhouse gases; and (iii) improvement in the energy efficiency of all economic sectors; and (B) to ensure that the United States maintains a technological lead in developing and deploying advanced energy technologies." ARPA-E issues this Funding Opportunity Announcement (FOA) under the programmatic authorizing statute codified at 42 U.S.C. § 16538. The FOA and any awards made under this FOA are subject to 2 C.F.R. Part 200 as amended by 2 C.F.R. Part 910. ARPA-E funds research on and the development of high-potential, high-impact energy technologies that are too early for private-sector investment. The agency focuses on technologies that can be meaningfully advanced with a modest investment over a defined period of time in order to catalyze the translation from scientific discovery to early-stage technology. For the latest news and information about ARPA-E, its programs and the research projects currently supported, see: http://arpa-e.energy.gov/. Program Overview: The aim of this ARPA-E program is to make a transformational change to the current state-of-the-art and improve advanced reactor (AR) designs with operations and maintenance (O&M) in mind.

OBJECTIVE: This is an AF Special Topic partnership, please see the above AF Special Topic instructions for further details. A Phase I award will be completed over 3 months with a maximum award of $25K and a Phase II may be awarded for a maximum period of 12 months DESCRIPTION: Academia is producing disruptive science and technology innovations at an increasingly rapid pace. Hence, rather than utilizing a pre-defined requirements approach, this topic is intended to be an open call for ideas and technologies that may not be currently listed (i.e. the unknown-unknown) under STTR topics, but nonetheless still fit within broad interest areas of the Air Force basic research level. These broad areas (Engineering and Complex Systems, Information and Networks, Physical Sciences, and Chemistry/Biological Sciences) are covered in greater detail at wpafb.af.mil/Welcome/Fact-Sheets/Display/Article/842026. To be eligible, offeror(s) must be teams that have formed companies and partnered with a university (e.g. university entrepreneurship centers, university technology transfer offices). The offeror should demonstrate their technical capability by demonstrating a credible and high-potential minimum viable product (MVP) along with a credible plan for developing the prototype to a commercially available solution. This topic is not looking for fully formed products, and it is acceptable if the solutions are earlier stage.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research. This solicitation limits the field to the following areas that stand to directly benefit from a grounding in formal methods: computer networks, cyber-human systems, distributed /operating systems, embedded systems, and machine learning. Other field(s) may emerge as priority areas for the program in future years, subject to the availability of funds.