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This Funding Opportunity Announcement (FOA) solicits Phase I (R43) Small Business Innovative Research (SBIR) grant applications from small business concerns (SBCs) to develop and/or adapt novel technologies to enable the characterization of human exposures to engineered nanomaterials (ENMs) and to monitor or assess ENMs in diverse media ranging from biological samples to air and water.  

As the nation continues to expand the horizon of opportunities and possibilities through advances in science, technology, engineering and mathematics (STEM), the need for a more diverse and well-prepared STEM workforce is also expanding1. The challenge of preparing citizens for the expanding workforce and the changing workplace environments calls for new innovations in STEM education

The purpose of the NSF Graduate Research Fellowship Program (GRFP) is to help ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing full-time research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) or in STEM education. The GRFP provides three years of support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM or STEM education. NSF especially encourages women, members of underrepresented minority groups, persons with disabilities, veterans, and undergraduate seniors to apply.

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 (seehttps://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 tothe Division of Emerging Frontiers in the Directorate for Biological Sciences (BIO/EF),once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors. The purpose of the Understanding the Rules of Life: Epigenetics (URoL:Epigenetics) program is to enable innovative research and to promote multidisciplinary education and workforce training in the broad area of epigenetics. The URoL:Epigenetics program is a widecollaborationacross Directorates/Offices within the National Science Foundation with a focus on understanding the relationship between epigenetic mechanisms associated with environmental change, the resultant phenotypes of organisms, and how these mechanisms lead to robustness and adaptability of organisms and populations. Understanding the Rules of Life (URoL): PredictingPhenotypeis one of NSF's 10 Big Ideasand is focused on predicting the set of observable characteristics (phenotype) from the genetic makeup of the individual and the nature of its environment.

Increasingly, undergraduate computer science (CS) programs are being called upon to prepare larger and more diverse student populations for careers in both CS and non-CS fields, including careers in scientific and non-scientific disciplines. Many of these students aim to acquire the understandings and competencies needed to learn how to  use computation collaboratively across different contexts and challenging problems. However, standard CS course sequences do not always serve these students well. With this solicitation, NSF will support teams of Institutions of Higher Education (IHEs) in re-envisioning the role of computing in interdisciplinary collaboration within their institutions. In addition, NSF will encourage partnering IHEs to use this opportunity to integrate the study of ethics into their curricula, both within core CS courses and across the relevant interdisciplinary application areas.

Quantum Leap Challenge Institutes are large-scale interdisciplinary research projects that aim to advance the frontiers of quantum information science and engineering. Research at these Institutes will span the focus areas of quantum computation, quantum communication, quantum simulation and/or quantum sensing. The institutes are expected to foster multidisciplinary approaches to specific scientific, technological, educational workforce development goals in these fields. Two types of awards will be supported under this program: (i) 12-month Conceptualization Grants (CGs) to support teams envisioning subsequent Institute proposals and (ii) 5-year Challenge Institute (CI) awards to establish and operate Quantum Leap Challenge Institutes. This activity is part of the Quantum Leap, one of the research Big Ideas promoted by the National Science Foundation (NSF). The NSF Quantum Leap Challenge Institutes program is consistent with the scope of NSF multidisciplinary centers for quantum research and education as described in the National Quantum Initiative Act[1]. In 2016, the NSF unveiled a set of "Big Ideas," ten bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (seehttps://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. Although proposals responding to this solicitation must be submitted tothe Office of Multidisciplinary Activities (OMA) in the Directorate of Mathematical and Physical Sciences (MPS),they will subsequently be managed by a cross-disciplinary team of NSF Program Directors.

A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications,healthcare informatics and business analytics. A salient feature of these emerging domains is the large and continuously streaming data sets that these applications generate, which must be processed efficiently enough to support real-time learning and decision making based on these data. This challenge requires novel hardware techniques and machine-learning architectures.This solicitation seeks to lay the foundation for next-generation co-design of RTML algorithms and hardware, with the principal focus on developing novel hardware architectures and learning algorithms in which all stages of training (including incremental training, hyperparameter estimation, and deployment) can be performed in real time. The National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA) are teaming up through this Real-Time Machine Learning (RTML) program to explore high-performance, energy-efficient hardware and machine-learning architectures that can learn from a continuous stream of new data in real time, through opportunities for post-award collaboration between researchers supported by DARPA and NSF.

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.

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. Through this solicitation, NSF is seeking to expand and sustain the network of Innovation Corps (I-CorpsTM) (hereinafter I-Corps) Nodes that work cooperatively to support the development of innovations that will benefit society. NSF plans to build upon the established National Innovation Network (consisting of I-Corps Nodes and Sites) to further support the needs for innovation research, education and training. The interconnected nodes of the network are expected to be diverse in research areas, resources, tools, programs, capabilities, and geographic locations - providing the network with the flexibility to grow or reconfigure as needs arise.

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.

The Human Cell Atlas (HCA) is a global effort to create a reference map of all cell types in the human body. The Chan Zuckerberg Initiative and the Helmsley Charitable Trust are pleased to announce continued support for the Human Cell Atlas by collaborating on two new funding mechanisms that the community can access through a single application portal. The Chan Zuckerberg Initiative seeks to continue the work of the HCA community with a focus on interdisciplinary work and collaboration through the formation of 3 year Seed Networks. The Helmsley Charitable Trust welcomes applications that will construct a detailed atlas of the human gut. Project Specifications This Request for Applications (RFA) seeks to support the continued growth of nascent projects and to incubate new networks. The Seed Networks should generate new tools, open source analysis methods, and significant contributions of diverse data types to the Human Cell Atlas Data Coordination Platform. Applications should have a primary focus on the healthy tissues that will contribute to a reference atlas. Seed Networks Seed Networks should consist of at least three principal investigators, including at least one computational biologist or software engineer, together with additional computational biologists, engineers, experimental biologists, and/or physicians. CZI Seed Networks aim to support foundational tools and resources for the HCA and will not require a gut component in the application. CZI Seed Network Grants have four overarching scientific goals: - Build and support networks of collaborating scientists and engineers; - Contribution of high-quality data to v1.0 of the HCA; - Development of new technologies and benchmark data sets, particularly those anchored in spatial as well as molecular information; - Support of computational biology within the Human Cell Atlas community.

A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications, healthcare informatics and business analytics.

The goal of the Sensing, Learning, Autonomy, and Knowledge Engineering (SLAKE) program is to advance Air Force sensing capabilities by employing diverse sensor processing results at a representational or product level that is abstracted from the direct sensing output yet retains crucial information and corresponding uncertainties. Key research areas under SLAKE include development of sensor product representations suitable for efficient storage, efficient communication, and efficient resource allocation; robust conversion of sensor processing output to novel representation formats; accurate characterization of sensing uncertainties; rigorous incorporation of sensing uncertainties within novel algorithms for sensor resource management, task allocation, and information fusion; development and employment of virtual environments suitable for exercising specific algorithms and for analyzing specific system concepts; and sustained, efficient descriptions of mission context and mission operating environment. In support of technology maturation and transition, SLAKE also includes small unmanned aerial system (SUAS) integration and operation, advanced demonstration and validation.

CADS invites research proposals from Tenure/Tenure Track Faculty members for its 2018 Research Fellowships. The fellowships provide support for Miami's faculty on projects broadly related to the area of analytics and data science. CADS will fund one proposal up to $25,000 for one year in duration. Topics should address problems, challenges, or questions that emerge in response to larger, more diverse, higher volume data. Multidisciplinary proposals featuring researchers from different academic divisions are strongly encouraged, with a minimum expectation of researchers representing different academic departments. Proposals comprised only of researchers from within a single academic department will not be considered.

The CISE Research Infrastructure (CRI) program drives discovery and learning in the core CISE disciplines of the three participating CISE divisions by supporting the creation and enhancement of world-class research infrastructure that will support focused research agendas in computer and information science and engineering. This infrastructure will enable CISE researchers to advance the frontiers of CISE research. Further, through the CRI program, CISE seeks to ensure that individuals from a diverse range of academic institutions, including minority-serving and predominantly undergraduate institutions, have access to such infrastructure.

This solicitation seeks proposals to support the diverse network-dependent research and operationalrequirementsof vessels in the U.S. Academic Research Fleet (ARF) and associated platforms by providing satellite communication system(s) that can be used as one of multiple options for at-sea access to the Internet.

The purpose of the NSF Graduate Research Fellowship Program (GRFP) is to help ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing full-time research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) or in STEM education. The GRFP provides three years of support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM or STEM education. NSF especially encourages women, members of underrepresented minority groups, persons with disabilities, veterans, and undergraduate seniors to apply.

This Funding Opportunity Announcement (FOA) solicits grant applications proposing exploratory research projects focused on the early-stage development of highly innovative technologies that improve the quality of the samples used for cancer research or clinical care. This includes new capabilities to address issues related to pre-analytical degradation of targeted analytes during the collection, processing, handling, and/or storage of cancer-relevant biospecimens. The overall goal is to support the development of highly innovative technologies capable of maximizing or otherwise interrogating the quality and utility of biological samples used for downstream analyses. This FOA will support the development of tools, devices, instrumentation, and associated methods to preserve or protect sample integrity, or establish verification criteria for quality assessment/quality control and handling under diverse conditions. These technologies are expected to accelerate and/or enhance research in cancer biology, early detection and screening, clinical diagnosis, treatment, epidemiology, or address issues associated with cancer health disparities, by reducing pre-analytical variations that affect biospecimen sample quality.

The MPS DC is expected to be the central clearinghouse for TC data management, and will incorporate novel approaches and technologies for data management, data mining and meta-analyses, and data sharing across many organs and tissues, diseases, data types, and TC platforms. The MPS Data center is expected to provide different levels of public and tiered access to TC information for basic and clinical researchers, academic and practicing physicians, the pharmaceutical industry, NIH, FDA and other government agencies, patients, and the lay public. The MPS Data Center will work with IQ Consortium members to develop and make available a secure, customizable coordinated data management system for collection, storage, and analyses of diverse data types from multiple TC platforms being developed and used for drug screening, safety and efficacy testing.

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and enabling 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, although when responding to this solicitation proposals must be submitted to the Division of Emerging Frontiers in the Directorate for Biological Sciences (BIO/EF), upon receipt proposals will be managed by a cross-Directorate team of NSF Program Directors. A full list of the Understanding the Rules of Life awards can be found on the NSF Awards Search.