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As computing has become an integral part of the practice of modern science, technology, engineering and mathematics (STEM), the STEM + Computing Partnerships program seeks to address the urgent need to prepare students from the early grades through high school in the essential skills, competencies, and dispositions needed to succeed in a computationally-dependent world. Thus, STEM+C advances the integration of computational thinking and computing activities in early childhood education through high school (pre-K-12) to provide a strong and developmental foundation in computing and computational thinking through the integration of computing in STEM teaching and learning, and/or the applied integration of STEM content in pre-K-12 computer science education.

This Funding Opportunity Announcement (FOA) solicits applications from single institutions, or consortia of institutions, to participate in a network of research groups developing computational models of immunity to infectious diseases other than HIV/AIDS. Applications are sought to develop, refine and validate computational models of immune responses (1) during or following infection, and/or (2) before and after vaccination against an infectious disease, through an iterative approach involving computational studies and immunological experimentation. The main goal of this FOA is to advance our understanding of the complex immune mechanisms triggered by infection and/or vaccination through the development and application of computational models of immunity, coupled with immunological experimentation to validate and improve the utility and robustness of the computational models.Another goal of this FOA is to make the computational models and data developed under this initiative readily available to the broader research community for further refinement or direct use in biological experimentation. This program will also support pilot projects, workshops, and symposia to foster the use of computational models of immunity by the broader research community.

This Funding Opportunity Announcement (FOA) solicits applications from single institutions, or consortia of institutions, to participate in a network of research groups developing computational models of immunity to infectious diseases other than HIV/AIDS. Applications are sought to develop, refine and validate computational models of immune responses (1) during or following infection, and/or (2) before and after vaccination against an infectious disease, through an iterative approach involving computational studies and immunological experimentation. The main goal of this FOA is to advance our understanding of the complex immune mechanisms triggered by infection and/or vaccination through the development and application of computational models of immunity, coupled with immunological experimentation to validate and improve the utility and robustness of the computational models.  Another goal of this FOA is to make the computational models and data developed under this initiative readily available to the broader research community for further refinement or direct use in biological experimentation. This program will also support pilot projects, workshops, and symposia to foster the use of computational models of immunity by the broader research community.  

In 2013, a new NSF-funded petascale computing system, Blue Waters, was deployed at the University of Illinois. The goal of this project and system is to open up new possibilities in science and engineering by providing computational capability that makes it possible for investigators to tackle much larger and more complex research challenges across a wide spectrum of domains. The purpose of this solicitation is to invite research groups to submit requests for allocations of resources on the Blue Waters system. Proposers must show a compelling science or engineering challenge that will require petascale computing resources. Proposers must also be prepared to demonstrate that they have a science or engineering research problem that requires and can effectively exploit the petascale computing capabilities offered by Blue Waters. Proposals from or including junior researchers are encouraged, as one of the goals of this solicitation is to build a community capable of using petascale computing.

In 2013, a new NSF-funded petascale computing system, Blue Waters, was deployed at the University of Illinois.  The goal of this project and system is to open up new possibilities in science and engineering by providing computational capability that makes it possible for investigators to tackle much larger and more complex research challenges across a wide spectrum of domains.  The purpose of this solicitation is to invite research groups to submit requests for allocations of resources on the Blue Waters system. Proposers must show a compelling science or engineering challenge that will require petascale computing resources. Proposers must also be prepared to demonstrate that they have a science or engineering research problem that requires and can effectively exploit the petascale computing  capabilities offered by Blue Waters.  Proposals from or including junior researchers are encouraged, as one of the goals of this solicitation is to build a community capable of using petascale computing.

This Funding Opportunity Announcement (FOA) solicits applications developing computational models of immunity that advance understanding of the mechanisms required to induce and/or maintain protective immunity to infectious pathogens, other than HIV, and/or vaccines against such pathogens. The main goal of this FOA is to advance development and application of computational models of immunity that are refined through iterative immunological experimentation to validate and improve the utility and robustness of the computational models. Another goal of this FOA is to make the computational models and data developed under this initiative readily available to the broader research community for further refinement or direct use in biological experimentation. This program will also support workshops and symposia to foster the use of computational models of immunity by the broader research community.

The functionality of the NeuroImaging Tools and Resources Collaboratory (NITRC) has enabled three distinct components to flourish: Resources Registry (NITRC-R): a collaboratory enabling the distribution, enhancement, and adoption of neuroimaging tools and resources. Image Repository (NITRC-IR): a curated repository of free neuroimaging datasets meeting global standards. Computational Environment (NITRC-CE): a freely downloadable or pay-as-you-go virtual computing cloud-based platform that is pre-configured with popular neuroimaging tools. NITRC-R has become the major web-based collaborative environment enabling the distribution, enhancement, and adoption of neuroinformatics resources. It currently hosts more than 1,000 tools and resources in areas such as magnetic resonance imaging (MRI), computed tomography (CT), optical imaging, positron emission tomography/single-photon emission computed tomography (PET/SPECT), electroencephalography/magnetoencephalography/electrocorticography (EEG/MEG/ECoG), computational neuroscience, and imaging genomics. Since NITRC's inception, there have been more than 10 million total downloads of tools from NITRC-R.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II).  Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering.  Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies.  Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II). Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering. Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies. Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

Computational neuroscience provides a theoretical foundation and a rich set of technical approaches for understanding complex neurobiological systems, building on the theory, methods, and findings of computer science, neuroscience, and numerous other disciplines. Through the CRCNS program, the National Science Foundation (NSF), the National Institutes of Health (NIH), the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF), the French National Research Agency (Agence Nationale de la Recherche, ANR), and the United States-Israel Binational Science Foundation (BSF) support collaborative activities that will advance the understanding of nervous system structure and function, mechanisms underlying nervous system disorders, and computational strategies used by the nervous system. 

Advanced computational infrastructure and the ability to perform large-scale simulations and accumulate massive amounts of data have revolutionized scientific and engineering disciplines.  The goal of the CDS&E program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data analysis approaches.  The intellectual drivers may be in an individual discipline or they may cut across more than one discipline in various Directorates.  The key identifying factor is that the outcome relies on the development, adaptation, and utilization of one or more of the capabilities offered by advancement of both research and infrastructure in computation and data, either through cross-cutting or disciplinary programs. 

The NIH is interested in promoting a broad base of research and development of technologies in biomedical computing, informatics, and Big Data Science that will support rapid progress in areas of scientific opportunity in biomedical research. It is expected that this research and development is conducted in the context of important biomedical and behavioral research problems. As such, applications are intended to develop enabling technologies that could apply to the interests of most NIH Institutes and Centers and range from basic biomedicine and including research to all relevant organ systems and diseases. Major themes of research include collaborative environments; data integration; analysis and modeling methodologies; and novel computer science and statistical approaches. New opportunities are also emerging as large and complex data sets are becoming increasingly available to the research community. This initiative aims to address biomedical research areas in biomedical computing, informatics, and Big Data science through the early stage development of new software, tools and related resources, as well as the fundamental research (e.g., methodologies and approaches) leading up to that development.

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Programs, or Core Programs, or Disciplinary Programs), which include: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The CMMT program supports fundamental research that advances conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated analytical, computational, and data-centric techniques; and predictive materials-specific theory, simulation, and modeling for materials research.Research may encompass the advance of new paradigms in materials research, including emerging data-centric approaches utilizing data-analytics or machine learning. Computational efforts span from the level of workstations to advanced and high-performance scientific computing. Emphasis is on approaches that begin at the smallest appropriate length scale, such as electronic, atomic, molecular, nano-, micro-, and mesoscale, required to yield fundamental insight into material properties, processes, and behavior, to predict new materials and states of matter, and to reveal new materials phenomena. Approaches that span multiple scales of length and time may be required to advance fundamental understanding of materials properties and phenomena, particularly for polymeric materials and soft matter.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II). Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering. Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies. Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II). Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering. Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies. Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science. The solicitation invites two types of proposals: "Foundations" (F): those developing or studying fundamental theories, techniques, methodologies, technologies of broad applicability to Big Data problems; and "Innovative Applications" (IA): those developing techniques, methodologies and technologies of key importance to a Big Data problem directly impacting at least one specific application. Therefore, projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc. While Innovative Applications (IA) proposals may address critical big data challenges within a specific domain, a high level of innovation is expected in all proposals and proposals should, in general, strive to provide solutions with potential for a broader impact on data science and its applications. IA proposals may focus on novel theoretical analysis and/or on experimental evaluation of techniques and methodologies within a specific domain. Proposals in all areas of sciences and engineering covered by participating directorates at NSF are welcome.

Computational neuroscience provides a theoretical foundation and a rich set of technical approaches for understanding complex neurobiological systems, building on the theory, methods, and findings of computer science, neuroscience, and numerous other disciplines. Through the CRCNS program, the National Science Foundation (NSF), the National Institutes of Health (NIH), the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF), the French National Research Agency (Agence Nationale de la Recherche, ANR), the United States-Israel Binational Science Foundation (BSF), and Japan's National Institute of Information and Communications Technology (NICT) support collaborative activities that will advance the understanding of nervous system structure and function, mechanisms underlying nervous system disorders, and computational strategies used by the nervous system.

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.

The primary objective of this FOA is to stimulate innovative Convergent Neuroscience (CN) approaches to establish causal and/or probabilistic linkages across contiguous levels of analysis (e.g., gene, molecule, cell, circuit, system, behavior) in an explanatory model of psychopathology. In particular, applicants should focus on how specific constituent biological processes at one level of analysis contribute to quantifiable properties at other levels, either directly or as emergent phenomena.  Although not required, it is preferable that applications link at least three levels of analysis and include an emphasis on genetics. The projects under this FOA will develop novel methods, theories, and approaches through a CN team framework, bringing together highly synergistic inter/transdisciplinary teams from neuroscience and "orthogonal" fields (e.g., data/computational science, physics, engineering, mathematics, and environmental sciences). Successful teams will combine, expand upon, or develop conceptual frameworks and theoretical approaches, and build explanatory computational models that connect contiguous levels of analysis. Such frameworks, theories, and computational explanatory models should be validated through experimental approaches to elucidate biological underpinnings of complex behavioral (including cognitive and affective) outcomes in psychopathology. Additionally, a goal of this program is to advance research in CN by creating a shared community framework of resources which may be used by the broader research community to further research, as such, successful team will have robust plan for sharing data and other resources.