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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.

The Long Term Research in Environmental Biology (LTREB) Program supports the generation of extended time series of data to address important questions in evolutionary biology, ecology, and ecosystem science. Research areas include, but are not limited to, the effects of natural selection or other evolutionary processes on populations, communities, or ecosystems; the effects of interspecific interactions that vary over time and space; population or community dynamics for organisms that have extended life spans and long turnover times; feedbacks between ecological and evolutionary processes; pools of materials such as nutrients in soils that turn over at intermediate to longer time scales; and external forcing functions such as climatic cycles that operate over long return intervals. The Program intends to support decadal projects. Funding for an initial, 5-year period requires submission of a preliminary proposal and, if invited, submission of a full proposal that includes a 15-page project description. Proposals for the second five years of support (renewal proposals) are limited to an eight-page project description and do not require a preliminary proposal. Continuation of an LTREB project beyond an initial ten year award will require submission of a new preliminary proposal that presents a new decadal research plan.?? Successful LTREB proposals address three essential components: A Decadal Research Plan that clearly articulates important questions that cannot be addressed with data that have already been collected, but could be answered if ten additional years of data were collected. This plan is not a research timeline or management plan. It is a concise justification for ten additional years of support in order to advance understanding of key concepts, questions, or theories in environmental biology.Core Data: LTREB proposals require that the author has studied a particular phenomenon or process for at least six years up to the present or for long enough to gene

The Division of Engineering Education and Centers (EEC) supports creation of a more agile engineering education ecosystem, equally open and available to all members of society, that dynamically and rapidly adapts to meet the changing needs of society and the nation's economy.  Research is sought that will inform systemic change across all parts of the ecosystem

Shell is a leading oil and gas producer in the deepwater Gulf of Mexico, a recognized pioneer in oil and gas exploration and production technology and one of America's leading oil and natural gas producers, gasoline and natural gas marketers and petrochemical manufacturers. Focus on energy awareness with special publics, increasing interest in technical careers among students and professional development in science and math among educators. We support K-12 programs that boost math and science skills, as well as university programs that aid engineering and geoscience students and departments. Shell funds projects at vocational and technical schools where chemical and refinery operators and technicians are trained. We are especially interested in supporting educational outreach in math, science and technology to women/minority students and academic institutions with ethnically diverse enrollments. Focus on biodiversity initiatives with support to programs that restore critical ecosystems, address water, air quality research, preserve wetlands and sponsor wetlands initiatives. As part of our commitment to environmental stewardship, we support projects that restore and protect critical ecosystems. In addition to restoration and preservation efforts, we fund research projects for threatened wildlife and/or habitats.

The Long Term Research in Environmental Biology (LTREB) Program supports the generation of extended time series of data to address important questions in evolutionary biology, ecology, and ecosystem science. Research areas include, but are not limited to, the effects of natural selection or other evolutionary processes on populations, communities, or ecosystems; the effects of interspecific interactions that vary over time and space; population or community dynamics for organisms that have extended life spans and long turnover times; feedbacks between ecological and evolutionary processes; pools of materials such as nutrients in soils that turn over at intermediate to longer time scales; and external forcing functions such as climatic cycles that operate over long return intervals.

VentureWell Faculty Grants provide up to $30,000 to help fund and support faculty with innovative ideas to create new or transform existing courses and programs to help students develop novel, STEM-based inventions and gain the necessary entrepreneurial skills needed to bring these ideas to market. We will be seeking proposals for areas that will support the emerging generation of inventors and innovators and the i&e ecosystems critical to their success. Successful grant proposals include: - A focus on technology entrepreneurship - Experiential learning by doing, and creative approaches to solving real world problems, - The formation of student teams focused on technology inventions with positive social and/or environmental impact - A supportive entrepreneurial ecosystem for student teams to pursue commercialization - A plan for continuation of the course or program after VentureWell funding

The Hydrologic Sciences Program supports basic research on the fluxes of water in the terrestrial environment that constitute the water cycle as well as the mass and energy transport function of the water cycle. The Program supports the study of processes including (but not limited to): rainfall, runoff, infiltration and streamflow; evaporation and transpiration; the flow of water in soils and aquifers; and the transport of suspended, dissolved, and colloidal components. The Program is interested in how water interacts with the landscape and the ecosystem as well as how the water cycle and its coupled processes are altered by land use and climate. Studies may address physical, chemical, and/or biological processes that are coupled directly to water transport. Observational, experimental, theoretical, modeling, synthesis and field approaches are supported. Projects submitted to Hydrologic Sciences commonly involve expertise from physical and ecosystem sciences, engineering and/or mathematics; and proposals may require joint review with related programs.

The National Science Foundation (NSF) seeks to develop and nurture a national innovation ecosystem that builds upon fundamental research to guide the output to facilitate the application of scientific discoveries closer to the development of technologies, products and processes that benefit society. In order to maintain, strengthen and grow a national innovation ecosystem, NSF has established the Innovation Corps - National Innovation Network Teams Program (I-Corps Teams). The NSF I-Corps Teams Program purpose is to identify NSF-funded researchers who will receive additional support in the form of entrepreneurial education, mentoring and funding to accelerate innovation that can attract subsequent third-party funding. The purpose of the NSF I-Corps Teams grant is to give the project team access to resources to help determine the readiness to transition technology developed by previously-funded or currently funded NSF projects. The outcomes of I-Corps Teams projects will be threefold: 1) a clear go /or no go decision regarding viability of products and services, 2) should the decision be to move the effort forward, a transition plan for those projects to move forward, and 3) a definition of a compelling technology demonstration for potential partners.

In FY 2016, the Big Data Regional Innovation Hubs: Establishing Spokes to Advance Big Data Applications (BD Spokes) solicitation began extending the BD Hubs network by establishing multi-institutional and multi-sector collaborations to focus on topics of specific interest to a given region. The first set of BD Spokes was funded in FY 2016. This solicitation calls for new BD Spoke proposals to be awarded in FY 2018. Collaborating with BD Hubs, each BD Spoke will focus on a particular topic that requires Big Data approaches and solutions. The set of activities managed by a BD Spoke will promote progress towards solutions in the chosen topic area. The regional BD Hub Steering Committee will provide general guidance to each BD Spoke and will assist the BD Spoke in coordinating with the national BD Hub network, with other BD Spokes, and with the broader innovation ecosystem.

To continue to strengthen the innovation ecosystem, NSF is revising NSF 12-511 to promote two choices under the Partnerships for Innovation (PFI): Accelerating Innovation Research (AIR) subprogram.  The first choice, Technology Translation, encourages the translation of technologically-promising research discoveries made by prior and/or current NSF-funded investigators toward a path of commercialization; while the second choice, Research Alliance, promotes synergistic collaborations between an existing NSF-funded research alliance (including consortia such as Engineering Research Centers, Industry University Cooperative Research Centers, Science and Technology Centers, Nanoscale Science and Engineering Centers, Materials Research Science and Engineering Centers, Centers for Chemical Innovation, and Emerging Frontiers in Research and Innovation grantees) and other public and private entities to motivate the translation and transfer of research discoveries into innovative technologies and commercial reality.  Both of these choices are designed to accelerate innovation that results in the creation of new wealth and the building of strong local, regional, and national economies.

The Platforms for Advanced Wireless Research (PAWR) program aims to support advanced wireless research platforms conceived by the U.S. academic and industrial wireless research community. PAWR will enable experimental exploration of robust new wireless devices, communication techniques, networks, systems, and services that will revolutionize the nation's wireless ecosystem, thereby enhancing broadband connectivity, leveraging the emerging Internet of Things (IoT), and sustaining US leadership and economic competitiveness for decades to come.

The Scalable Parallelism in the Extreme (SPX) program aims to support research addressing the challenges of increasing performance in this modern era of parallel computing. This will require a collaborative effort among researchers in multiple areas, from services and applications down to micro-architecture. SPX encompasses all five NSCI Strategic Objectives, including supporting foundational research toward architecture and software approaches that drive performance improvements in the post-Moore's Law era; development and deployment of programmable, scalable, and reusable platforms in the national HPC and scientific cyberinfrastructure ecosystem; increased coherence of data analytic computing and modeling and simulation; and capable extreme-scale computing. Coordination with industrial efforts that pursue related goals are encouraged.

EPA-ORD seeks applications from eligible entities to enter into a cooperative agreement with EPA that will provide training opportunities for undergraduate and graduate students on-site at ORD's Ground Water and Ecosystems Research Division (GWERD) research facilities located in Ada, Oklahoma.  It is envisioned that the training program will increase both the effectiveness and number of future environmental scientists. The training received under the mentorship of EPA scientists will complement the trainees' academic coursework. The recipient will be responsible for ensuring that the training projects are supportive of the trainees' academic training.  Some appropriate fields of study for trainees include, but are not limited to, environmental science, water policy, chemistry, engineering, computer science, ecology, and physical and biological sciences.

Advancements in data-driven scientific research depend on trustworthy and reliable cyberinfrastructure. Researchers rely on a variety of networked technologies and software tools to achieve their scientific goals. These may include local or remote instruments, wireless sensors, software programs, operating systems, database servers, high-performance computing, large-scale storage, and other critical infrastructure connected by high-speed networking. This complex, distributed, interconnected global cyberinfrastructure ecosystem presents unique cybersecurity challenges. NSF-funded scientific instruments, sensors and equipment are specialized, highly-visible assets that present attractive targets for both unintentional errors and malicious activity; untrustworthy software or a loss of integrity of the data collected by a scientific instrument may mean corrupt, skewed or incomplete results. Furthermore, often data-driven research, e.g., in the medical field or in the social sciences, requires access to private information, and exposure of such data may cause financial, reputational and/or other damage.

The National Science Foundation (NSF) seeks to further develop and nurture a national innovation ecosystem that builds upon fundamental research to guide the output of scientific discoveries closer to the development of technologies, products, processes and services that benefit society. The goal of the program is to dramatically reduce the period of time necessary to bring a promising idea from its inception to widespread implementation.

The GLCPC is seeking innovative proposals that fall into four categories: Scaling studies: The scaling of codes which will operate efficiently on large numbers of parallel processors presents a number of challenges.  Therefore, projects of particular interest include those that optimize and/or scale community codes to very large scales. Examples include scaling of multilevel parallel applications (MPI+OpenMP), accelerators (CUDA, OpenACC or OpenCL), I/O and Data intensive applications, or novel communication topologies.  Multi-GLCPC-institutional projects addressing focused scientific projects. An example might be a Great Lakes Ecosystems Modeling initiative (Digital Great Lakes). Proposals for applications well-suited for the BW system architecture. Proposals from non-traditional and underserved communities.  

The National Science Foundation (NSF) seeks to develop and nurture a national innovation ecosystem that builds upon research to guide the output of scientific discoveries closer to the development of technologies, products and processes that benefit society.

The ERC program supports convergent research that will lead to strong societal impact. Each ERC has interacting foundational components that go beyond the research project, including engineering workforce development at all participant stages, a culture of diversity and inclusion where all participants gain mutual benefit, and value creation within an innovation ecosystem that will outlast the lifetime of the ERC. The logical reasoning that links the proposed activities to the identified goals for each ERC should be clear.

The Partnerships for Innovation (PFI) Program within the Division of Industrial Innovation and Partnerships (IIP) offers researchers from all disciplines of science and engineering funded by NSF the opportunity to perform translational research and technology development, catalyze partnerships and accelerate the transition of discoveries from the laboratory to the marketplace for societal benefit. PFI has five broad goals, as set forth by the American Innovation and Competitiveness Act of 2017 ("the Act", S.3084 - 114th Congress; Sec. 602. Translational Research Grants): (1) identifying and supporting NSF-sponsored research and technologies that have the potential for accelerated commercialization; (2) supporting prior or current NSF-sponsored investigators, institutions of higher education, and non-profit organizations that partner with an institution of higher education in undertaking proof-of-concept work, including the development of technology prototypes that are derived from NSF-sponsored research and have potential market value; (3) promoting sustainable partnerships between NSF-funded institutions, industry, and other organizations within academia and the private sector with the purpose of accelerating the transfer of technology; (4) developing multi-disciplinary innovation ecosystems which involve and are responsive to the specific needs of academia and industry; (5) providing professional development, mentoring, and advice in entrepreneurship, project management, and technology and business development to innovators.

NSF's Directorate for Computer and Information Science and Engineering (CISE) initiated the National Network of Big Data Regional Innovation Hubs (BD Hubs) program in FY 2015 (NSF 15-562). Four Big Data Hubs (BD Hubs)-Midwest, Northeast, South, and West-were established, one in each of the four Census Regions of the United States [1]. The BD Hubs provide the ability to engage local or regional stakeholders, e.g., city, county, and state governments, local industry and non-profits, and regional academic institutions, in big data research, and permit a focus on regional issues. These collaborative activities and partnerships play a critical role in building and sustaining a successful national big data innovation ecosystem.