OARS funding Computer

This funding opportunity enables engineering departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome long-standing issues in their undergraduate programs and educate inclusive communities of engineering students prepared to solve 21st century challenges.  Computer science departments, whether administratively located in or outside an engineering program, are included in RED, as they share the same challenges as traditional engineering departments.

Hazards SEES seeks research projects that will productively cross the boundaries of the atmospheric and geospace, earth, and ocean sciences; computer and information science (including cyberinfrastructure); engineering; mathematics and statistics; and social, economic, and behavioral sciences. Successful proposals will integrate across multiple disciplines to promote research that advances new paradigms that contribute to creating a society resilient to hazards.

The Trust Challenge funds successful collaborations or "laboratories" where challenges to trust in connected learning environments can be identified and addressed. Successful labs will create scalable, innovative, and transformative exemplars of connected learning that bridge technological solutions with complex social considerations of trust.

The Allen Distinguished Investigator (ADI) Program seeks to fund a select group of investigators to pursue new, pioneering research in academic settings that, collectively, 'move the needle' towards answering broad scientific questions. The most promising proposals will incorporate novel, creative, and ambitious approaches. For this reason, the program is especially interested in proposals that are unlikely to receive funding from traditional governmental sources.   For 2014, the Foundation will make awards in two areas: Life Sciences and Artificial Intelligence (AI). (Information regarding the ADI for Life Sciences will be announced at a later date.)   We are pleased to announce the Artificial Intelligence awards will focus on three fundamental topics:   Machine Reading Diagram Interpretation Spatial and Temporal Reasoning

The purpose of this Funding Opportunity Announcement (FOA) is to solicit revisions (competitive supplements) to add a Big Data Science track to active T15 institutional training grants for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with biomedical Big Data in the biomedical sciences (see definition under Funding Opportunity Description). This proposed training initiative should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical data.

The purpose of this Funding Opportunity Announcement (FOA) is to solicit revisions (competitive supplements) to add a Big Data Science track to currently funded T32 institutional training grants for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with biomedical Big Data in the biomedical sciences (see definition under Funding Opportunity Description). This proposed training initiative should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical data.

Projects can be small to mid-scale - the key here is to show how we can involve the global research and development community in furthering science on the web, while testing what the right level of engagement is.  Any research-oriented software development project is eligible, with special consideration given to projects that further open, collaborative, reproducible research, and reusable tools and technology for open science. Candidate research projects should: Have a clearly stated and specific goal to achieve or problem to solve in software. Be directly relevant to your ongoing or shortly upcoming research. Require code that is sharable and reusable, with preference given to open source projects. Science team should be prepared to communicate regularly with the software team.

The goal of the Office of Science Graduate Student Research (SCGSR) program is to prepare graduate students for science, technology, engineering, or mathematics (STEM) careers critically important to the DOE Office of Science mission, by providing graduate thesis research opportunities at DOE laboratories.  The SCGSR program provides supplemental awards to outstanding U.S. graduate students to pursue part of their graduate thesis research at a DOE laboratory in areas that address scientific challenges central to the Office of Science mission. The research opportunity is expected to advance the graduate students' overall doctoral thesis while providing access to the expertise, resources, and capabilities available at the DOE laboratories.

The purpose of this Funding Opportunity Announcement (FOA) is to solicit applications for graduate training programs in Big Data Science, for the expressed purpose of training the next generation of scientists who will develop computational and quantitative approaches and tools needed by the biomedical research community to work with biomedical Big Data in the biomedical sciences (see definition under Funding Opportunity Description). This proposed training initiative should prepare qualified individuals for careers in developing new technologies and methods that will allow biomedical researchers to maximize the value of the growing volume and complexity of biomedical data.

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.

The goals of the Resilient Interdependent Infrastructure Processes and Systems (RIPS) solicitation are (1) to foster an interdisciplinary research community that discovers new knowledge for the design and operation of infrastructures as processes and services  (2) to enhance the understanding and design of interdependent critical infrastructure systems (ICIs) and processes that provide essential goods and services despite disruptions and failures from any cause, natural, technological, or malicious, and (3) to create the knowledge for innovation in ICIs to advance society with new goods and services. The objectives of this solicitation are: Create theoretical frameworks and multidisciplinary computational models of interdependent infrastructure systems, processes and services, capable of analytical prediction of complex behaviors, in response to system and policy changes. Synthesize new approaches to increase resilience, interoperations, performance, and readiness in ICIs. Understand organizational, social, psychological, legal, political and economic obstacles to improving ICI's, and identifying strategies for overcoming those obstacles. The RIPS solicitation seeks proposals with transformative ideas that will ensure ICIs services are effective, efficient, dependable, adaptable, resilient, safe, and secure.  Successful proposals are expected to study multiple infrastructures focusing on them as interdependent systems that deliver services, enabling a new interdisciplinary paradigm in infrastructure research.  Proposals that do not broadly integrate across the cyber-physical, engineering and social, behavioral and economic (SBE) sciences may be returned without review. 

This fall, OARS will host a series of brown-bag workshops on navigating the NSF proposal process.  Workshops will be held select Tuesdays from noon to 1:00pm in Pearson 208.  You are welcome to attend any or all of the sessions.  Click through for dates and registration information.

The Office of Fusion Energy Sciences (FES) of the Office of Science (SC), U.S. Department of Energy (DOE), announces its interest in receiving new or renewal grant applications for theoretical and computational research relevant to the U.S. magnetic fusion energy sciences program. Applications selected in response to this FOA will be funded in Fiscal Year 2015, subject to the availability of appropriated funds. The specific areas of interest are: 1. Macroscopic Stability 2. Confinement and Transport 3. Boundary Physics 4. Plasma Heating & Non-inductive Current Drive, and 5. Energetic Particles Specific information about each topical area is included in the Supplementary information section of the full Funding Opportunity Announcement (FOA) document. Due to the limited availability of funds, Principal Investigators with continuing theory grants may not submit a new application in the same topical areas as their existing grant. A Principal Investigator may submit only one application in response to this FOA, but applications can target multiple topical areas. 

In response to the spectacular opportunities and immense challenges presented by the dawning era of "Big Data" in biomedical research, NIH has developed the Big Data to Knowledge (BD2K) initiative with the mission of enabling the biomedical research community to use the various types of Big Data for research. The purpose of this Funding Opportunity Announcement (FOA) is to solicit development of analysis methods and software in the four topic areas of data compression/reduction, data visualization, data provenance, and data wrangling as part of the overall BD2K initiative.

The "Campus Cyberinfrastructure - Infrastructure, Innovation and Engineering (CC*IIE)" program invests in improvements and re-engineering at the campus level to support a range of data transfers supporting computational science and computer networks and systems research. The program also supports Network Integration activities tied to achieving higher levels of performance, reliability and predictability for science applications and distributed research projects. CC*IIE awards will be made in six areas. Data Driven Networking Infrastructure for the Campus and Researcher awards will be supported at up to $500,000 total for up to 2 years. Network Design and Implementation for Small Institutions awards will be supported at up to $350,000 total for up to two years. Network Integration and Applied Innovation awards will be supported at up to $1,000,000 total for up to 2 years. Identity and Access Management Integration awards will be supported at up to $300,000 total for up to two years. Campus CI Engineer awards will be made at up to $400,000 total for up to 2 years. Regional Coordination and Partnership in Advanced Networking awards will be made at up to $150,000 for up to 2 years.

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.  

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.

This funding opportunity announcement (FOA) encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that propose development of a broad base of innovative 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 to research in 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.

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 research-based master's and doctoral degrees in science and engineering. The GRFP provides three years of support for the graduate education of individuals who have demonstrated their potential for significant achievements in science and engineering.

The Advanced Scientific Computing Research (ASCR) program of the Office of Science (SC), U.S. Department of Energy (DOE), hereby invites proposals that will significantly improve our understanding of scientific workflow performance over extreme-scale networks and distributed computing infrastructures.