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The technology demonstrations that result from this BAA will substantially improve the Air Force's capability to conduct missions in a variety of environments while minimizing the risks to Airmen. The overall impact of integration of autonomous systems into the mission space will enable the Air Force to operate inside of the enemy's decision loop. STAT will develop and apply autonomy technologies to enhance the full mission cycle, including mission planning, mission execution, and post-mission analysis. Particular areas of interest include multi-domain command and control, manned-unmanned teaming, and information analytics. The technology demonstrations that result from this BAA will substantially improve the Air Force's capability to conduct missions in a variety of environments while minimizing the risks to Airmen. The overall impact of integration of autonomous systems into the mission space will enable the Air Force to operate inside of the enemy's decision loop. This effort plans to demonstrate modular, transferable, open system architectures, and deliver autonomy technologies applicable to a spectrum of multi-domain applications.

Lucozade Ribena Suntory (LRS) is seeking technologies to quantify bubbles and their size distribution in sugar-sweetened drinks containing at least 2% sugar. These lab-based techniques will enable LRS to determine which approaches to improving carbonation are the most effective.

The purpose of the Mentored Quantitative Research Career Development Award (K25) is to attract to NIH-relevant research those investigators whose quantitative science and engineering research has thus far not been focused primarily on questions of health and disease. The K25 award will provide support and "protected time" for a period of supervised study and research for productive professionals with quantitative (e.g., mathematics, statistics, economics, computer science, imaging science, informatics, physics, chemistry) and engineering backgrounds to integrate their expertise with NIH-relevant research. This Funding Opportunity Announcement (FOA) is designed specifically for applicants proposing to lead basic science experimental studies involving humans, referred to in NOT-OD-18-212 as prospective basic science studies involving human participants. These studies fall within the NIH definition of a clinical trial and also meet the definition of basic research. Types of studies that should submit under this FOA include studies that prospectively assign human participants to conditions (i.e., experimentally manipulate independent variables) and that assess biomedical or behavioral outcomes in humans for the purpose of understanding the fundamental aspects of phenomena without specific application towards processes or products in mind. Studies conducted with specific applications toward processes or products in mind should submit under the companion PA-18-395.

Although invention and proof-of-concept testing of new technologies are a key component of the BRAIN Initiative, to achieve their potential these technologies must also be optimized through feedback from end-users in the context of the intended experimental use. This seeks applications for the optimization of existing and emerging technologies and approaches that have potential to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and temporal scales, in any region and throughout the entire depth of the brain. This FOA is intended for the iterative refinement of emergent technologies and approaches that have already demonstrated their transformative potential through initial proof-of-concept testing, and are appropriate for accelerated development of hardware and software while scaling manufacturing techniques towards sustainable, broad dissemination and user-friendly incorporation into regular neuroscience practice. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Applications are expected to integrate appropriate domains of expertise, including where appropriate biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

Understanding the dynamic activity of neural circuits is central to the NIH BRAIN Initiative. This FOA seeks applications for proof-of-concept testing and development of new technologies and novel approaches for largescale recording and manipulation of neural activity to enable transformative understanding of dynamic signaling in the nervous system. In particular, we seek exceptionally creative approaches to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and/or temporal scales, in any region and throughout the entire depth of the brain. It is expected that the proposed research may be high-risk, but if successful could profoundly change the course of neuroscience research. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Where appropriate, applications are expected to integrate appropriate domains of expertise, including biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

This Funding Opportunity Announcement (FOA) solicits applications for a single Coordinating Center to support novel data acquisition strategies, data harmonization, analysis and dissemination activities on emerging and current drug abuse trends across the United States. The Coordinating Center will (1) Maintain a Scientific Advisory Group; (2) Maintain and refine an Early Warning Network composed of local experts on drug abuse data from the selected communities, as well as NIDA-supported community-based researchers, to assist in the ongoing monitoring and interpretation of data; (3) Maintain key community-level indicators for monitoring drug abuse trends and early identification of new synthetic drugs and emerging issues including establishing harmonization of indicators and of presentation and analysis of indicators across the selected communities; (4) Continue to identify and maintain novel sources of data including treatment admissions data, national drug use among adults and youth, law enforcement seizures, and drug poisoning death; (5) Conduct cross-site data analyses from the harmonized Coordinating Center data; (6) Continue to disseminate and identify novel ways to execute dissemination and publication plans of results and findings from the Coordinating Center data, including development and maintenance of a website for disseminating data and findings; (7) Conduct webinars on topics of interest to stakeholders; (8) Conduct on the ground epidemiologic investigations on topics of immediate crisis or need, providing functional feedback to impacted communities towards optimizing current and future response; (9) Provide operational, administrative and logistical support for the Coordinating Center data harmonization and dissemination initiative.

TheBIGDATAprogram seeks novel approaches in computer science, statistics, computational science, and mathematics leading towards the further development of the interdisciplinary field ofdata science.The program also seeks innovative applications in domain science, including social and behavioral sciences, education, physical sciences, and engineering, where data science and the availability of big data are creating new opportunities for research and insights not previously possible. The solicitation invites two categories of proposals: Foundations (BIGDATA: F):those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems, motivated by specific data challenges and requirements; and Innovative Applications (BIGDATA: IA):those engaged intranslational activities that employ new big data techniques, methodologies, and technologies to address and solve problems in specific application domains.

First Round of HPC4Mtls Solicitation is Now Open The first HPC4Mtls Program solicitation seeks concept papers that will address key challenges in developing, modifying, and/or qualifying new or modified materials that perform well in severe and complex energy application environments using high performance computing, modeling, simulation, and data analysis. For each of the program offices supporting this solicitation, we provide brief descriptions of their mission and the topics of interest to them. Deadline for concept paper submission is April 19, 2018 at 11:59 pm PDT.

The goals of the Accelerating Research through International Network-to-Network Collaborations (AccelNet) program are to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts. The program seeks to foster high-impact science and engineering by providing opportunities to create new collaborations and new combinations of resources and ideas among linked global networks.

The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in cyberinfrastructure. This program continues the CSSI program by removing the distinction between software and data elements/framework implementations, and instead emphasizing integrated cyberinfrastructure services, quantitative metrics with targets for delivery and usage of these services, and community creation.

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 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.

NIST is soliciting applications from eligible institutions of higher education in the U.S. and its territories that offer two- or four- year degrees in academic science, technology, engineering and mathematics (STEM) disciplines, which include but are not limited to biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical sciences, physics, and statistics, to establish and manage a program to support collaborative research relationships among NIST staff, undergraduate and graduate students, individuals with bachelor's or master's degrees, post-doctoral fellows, and academic affiliates, and the PREP researchers' academic institutions. These collaborative relationships will include research opportunities at the relevant NIST campuses in Boulder, Colorado (CO) (PREP Boulder), or Gaithersburg, Maryland (MD), and/or Charleston, South Carolina (SC) (PREP Gaithersburg). Eligible applicants may apply to establish and manage a PREP Boulder program or a PREP Gaithersburg program or may apply to establish and manage programs for both.

This NOFO will support achievement of national targets for 2018 antiretroviral therapy (ART) scale-up towards the UNAIDS Fast Track Targets in Ukraine. The recipient will implement innovative and effective recruitment and case management models for persons who inject drugs (PWID) and men who have sex with men (MSM) at the community level. These innovative changes will increase uptake of HIV community based testing and increase ART initiation for these populations. The recipient will pilot risk network-based testing using point-of-care recency assays to link recently infected PWID to care. The project will focus on the six regions with the highest HIV burden (Dnipropetrovsk, Mykolayiv, Odesa, government controlled areas (GCA) of Donetsk, Kyiv City, and Kherson) and continue to work in six additional medium burden oblasts (Cherkasy, Poltava, Chernihiv, Zaporizhzhya, Kirovohrad, and Kyiv). The recipient will also increase the capacity of the Government of Ukraine’s Center for Public Health (CPH) and regional monitoring and evaluation (M&E) centers specialists to conduct data analysis using statistical software and build institutional capacity to conduct economic evaluations of HIV interventions. Illustrative strategic information (SI) activities include development of trainings to support the Ministry of Health (MOH) and the newly established CPH in using statistical software, routine analysis of surveillance data, study design, and research protocol development.

The goal of the program is to support the "mathematical marketplace" by substantially increasing collaborative contacts between mathematicians. The foundation will make a large number of collaboration grants to accomplished, active researchers in the United States who do not otherwise have access to funding that allows support for travel and visitors. Awards will be based on the quality and significance of the applicant's previous research, as outlined in the Statement of Recent Work requirement below, and on the likely impact the collaboration grant will have on future research, both for the applicant and the applicant's graduate students and/or postdoctoral fellows. Other criteria include publication in high-quality journals, the applicant's current and recent Ph.D. students and the applicant's travel goals and general research activity.

The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets.  NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise, to develop improved survey methodologies for NCSES surveys, to create and improve indicators of S&T activities and resources, and strengthen methodologies to analyze and disseminate S&T statistical data. To that end, NCSES invites proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, workshops, experimental research, survey research and data collection and dissemination projects under its program for Research on the Science and Technology Enterprise:  Statistics and Surveys.

This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting dynamical features and patterns in complex brain data. It is expected that the tools developed under this FOA will be made widely available to the neuroscience research community for their use and modification. Investigative studies should be limited to validity testing of the tools being developed.

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.

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (see https://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted to the Education and Human Resources (EHR) Directorate/Division of Human Resource Development (HRD), once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors.

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (see https://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted to the Directorate for Engineering (ENG), Office of Emerging Frontiers and Multidisciplinary Activities (ENG/EFMA), once received the proposals will be managed by a cross-disciplinary team of NSF Program Directors.