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This Broad Agency Announcement (BAA) seeks to provide research and development for forming a revolutionary approach to information fusion and analysis by leveraging service-oriented architecture, open standards, and cutting-edge fusion and analytical algorithms to provide real-time (or near real-time) intelligence for decision makers. This BAA shall research and develop novel techniques to assist users with discovering the golden nuggets in the data - potential approaches include fusing diverse data sources, filtering noise, and leveraging pattern learning to derive patterns of life. Further, technical capabilities developed under this BAA will minimize user time spent gathering data and reporting data, while preserving and providing more time for analysis. This will be accomplished through several means to include a data framework that can easily and quickly connect to sundry data sources, a rich, intuitive personalized workspace and experience, a variety of user-defined visualization displays, machine learning to assist and automate mundane tasks, and a custom report generation tool.

Energy company Constellation believes that providing quality educational opportunities and career development are among the most important tools it can provide to communities to help them succeed over the long term.  To that end, the company is accepting grant applications for local community projects designed to inspire students to think differently about energy. Grants of up to $25,000 will be awarded for projects at the 6-12 grade level and up to $50,000 for projects at the college level. Projects should be team-oriented, learning-focused, hands-on demonstration projects that generate specific results and reach a minimum of a hundred students. 

The objective of this research is to develop guidance (tools, procedures, and policies) for identifying, evaluating, and communicating multimodal transportation investment right-sizing scenarios.  Although agencies are generally equipped to assess investment strategies, sufficient guidance is not readily available on how to identify and assess right-sizing or disinvestment scenarios in ways that clearly explain decisions associated with resource tradeoffs and constraints and how these decisions impact overall system resilience and sustainability.  Outcomes of this research should enable agencies to answer questions such as, "Why are we spending more or less on (or eliminating) a given asset; and why is that a good decision given the functional requirements of the broader transportation system"? 

The goals of the Network for Computational Nanotechnology (NCN) are to: 1) accelerate the transformation of nanoscience to nanotechnology through the integration of simulation with experimentation; 2) engage an ever-larger and more diverse cyber community sharing novel, high-quality nanoscale computation and simulation research and educational resources; 3) develop open-access, open-source software to stimulate data sharing; and 4) inspire and educate the next-generation workforce. The NCN consists of a stand-alone Cyber Platform, which provides computation, simulation, and education services to over 330,000 researchers, educators, students, and industry members of the nanoscience and engineering community annually worldwide; and Nodes, which develop compelling new computational and simulation tools to disseminate through Cyber Platform (nanoHUB.org) and cultivate communities of users in emerging areas of nanoscale science and engineering.

The goals of the Network for Computational Nanotechnology (NCN) are to: 1) accelerate the transformation of nanoscience to nanotechnology through the integration of simulation with experimentation; 2) engage an ever-larger and more diverse cyber community sharing novel, high-quality nanoscale computation and simulation research and educational resources; 3) develop open-access, open-source software to stimulate data sharing; and 4) inspire and educate the next-generation workforce. The NCN consists of a stand-alone Cyber Platform, which provides computation, simulation, and education services to over 330,000 researchers, educators, students, and industry members of the nanoscience and engineering community annually worldwide; and Nodes, which develop compelling new computational and simulation tools to disseminate through Cyber Platform

The Engineered Living Materials (ELM) program will develop design tools and methods that enable the engineering of structural features into cellular systems that function as living materials, thereby opening up a new design space for building technology.

The purpose of the BRAIN Initiative Fellows (F32) program is to enhance the research training of promising postdoctorates, early in their postdoctoral training period, who have the potential to become productive investigators in research areas that will advance the goals of the BRAIN Initiative. Applications are encouraged in any research area that is aligned with the BRAIN Initiative, including neuroethics. Applicants are expected to propose research training in an area that complements their predoctoral research. Formal training in quantitative perspectives and analytical tools is expected to be an integral part of the proposed research training plan. In order to maximize the training potential of the F32 award, this program encourages applications from individuals who have not yet completed their terminal doctoral degree and who expect to do so within 12 months of the application due date. On the application due date, candidates may not have completed more than 6 months of postdoctoral training.  

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

The Solar and Planetary Research Grants (SPG) Program provides individual investigator and collaborative research grants for observational, theoretical, laboratory, and archival data studies in the science of our solar system and extrasolar planetary systems. Proposals for projects and tools that enable and enhance research in those areas may also be submitted.

The mission of the JPC-1/MSIS is to explore the implications of models and technology for medical education and for the provision, management, and support of health services in the military. The JPC-1/MSIS plans, coordinates, and oversees a responsive world-class, tri-Service science and technology program focused on two areas of research. The first area, Medical Simulation and Training, is focused on improving military medical training through medical modeling, simulation, and educational training tools. The second area, Health Informatics and Information Technologies, is focused on improving the use and sharing of health-related data for better strategic planning, process development, and software applications.

The U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications proposing research that will contribute to an improved ability to understand and anticipate the public health and environmental impacts and behavioral drivers of significant changes in energy production and consumption in the United States, particularly those changes associated with advancing toward the deep decarbonization necessary to achieve national and international climate change mitigation objectives and avoid the most significant health, environmental, and economic impacts of climate change. The proposed research is intended to contribute to the development of new insights and predictive tools related to the multimedia, life-cycle impacts of the decarbonization of electricity generation; the electrification of end uses; the adoption of low-carbon emitting, renewable fuels; and the adoption of energy efficiency measures. The proposed research is also intended to contribute to an improved understanding of the drivers of individual, firm (i.e. business), and community decisions that affect energy consumption patterns, including decisions about the adoption of new technologies and energy efficiency measures.

The overarching goal of this FOA is to support the development of capabilities that will allow increased deployment of solar power generation at optimal cost. Better solar forecasting will allow the reduction of balancing, dispatch, and unit commitment costs associated with errors in the prediction of solar power generation. These costs scale with solar penetration, therefore it is important to keep them in check with advancements in the forecasting science, implementations of forecasting models with rapid execution, and seamless integration of forecasting tools in the electric system operations.

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 SI2 program focuses on supporting robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery. Thus, proposals are strongly encouraged to describe their approach to quality software development through a defined software engineering process that includes software testing, the appropriate use of analysis tools and capabilities such as those made available through the Software Assurance Marketplace (SWAMP, https://continuousassurance.org/), and collaborations with resources such as Software Carpentry (http://software-carpentry.org/) and the Center for Trustworthy Scientific Cyberinfrastructure (CTSC, http://trustedci.org/), in order to gain access to expertise where needed, such as in software design and engineering, as well as in cybersecurity.

The SD2 program aims to develop data-driven methods to accelerate scientific discovery and robust design in domains that lack complete models. Engineers regularly use high-fidelity simulations to create robust designs in complex domains such as aeronautics, automobiles, and integrated circuits. In contrast, robust design remains elusive in domains such as synthetic biology, neuro-computation, cyber, and polymer chemistry due to the lack of high-fidelity models. SD2 will develop tools to enable robust design despite the lack of complete scientific models.

The goal of the CPS program is to develop the core system science needed to engineer complex cyber-physical systems that people can use or interact with and depend upon. Some of these may require high-confidence or provable behaviors. The program aims to foster a research community committed to advancing research and education in CPS and to transitioning CPS science and technology into engineering practice. By abstracting from the particulars of specific systems and application domains, the CPS program seeks to reveal cross-cutting fundamental scientific and engineering principles that underpin the integration of cyber and physical elements across all application sectors. To expedite and accelerate the realization of cyber-physical systems in a wide range of applications, the CPS program also supports the development of methods, tools, and hardware and software components based upon these cross-cutting principles, along with validation of the principles via prototypes and testbeds. We have also seen a convergence of CPS technologies and research thrusts that underpin Smart & Connected Communities (S&CC) and the Internet of Things (IoT). These domains offer new and exciting challenges for foundational research and provide opportunities for maturation at multiple time horizons.

The Geotechnical Engineering and Materials Program (GEM) supports fundamental research in soil and rock mechanics and dynamics in support of physical civil infrastructure systems. Also supported is research on improvement of the engineering properties of geologic materials for infrastructure use by mechanical, biological, thermal, chemical, and electrical processes. The Program supports the traditional areas of foundation engineering, earth structures, underground construction, tunneling, geoenvironmental engineering, and site characterization, as well as the emerging area of bio-geo engineering, for civil engineering applications, with emphasis on sustainable geosystems. Research related to the geotechnical engineering aspects of geothermal energy and geothermal heat pump systems is also supported. The GEM program encourages knowledge dissemination and technology transfer activities that can lead to broader societal benefit and implementation for provision of physical civil infrastructure. The Program also encourages research that explores and builds upon advanced computing techniques and tools to enable major advances in Geotechnical Engineering.

Projects selected under this FOA will develop characterization tools, technologies, and or methodologies that improve the ability to predict geologic storage capacity within 30 percent, improve the utilization of the reservoir by understanding how faults and fractures in a reservoir affect the flow of CO2, and ensure storage permanence.

NIFA initiates a new challenge area to address critical water resources issues such as drought, excess soil moisture, flooding, quality and others in an agricultural context. Funding will be used to develop management practices, technologies, and tools for farmers, ranchers, forest owners and managers, public decision makers, public and private managers, and citizens to improve water resource quantity and quality. NIFA's approach will link social, economic, and behavioral sciences with traditional biophysical sciences and engineering to address regional-scale issues with shared hydrological processes and meteorological and basin characteristics.

For the Fund's first year, the Request For Proposals focuses on innovation in manufacturing processes for textiles and apparel as well as common manufacturing processes that apply to a broad range of consumer goods, such as small motor development and tooling for plastic injection molding.