OARS funding Computer

The advancement of sensing technology such as RGBD (Red Green Blue Depth), multi-camera and light field imaging systems, networks of sensors, advanced visual analytics and cloud computing will challenge the longstanding paradigms of capturing, creating, analyzing and utilizing visual information. Advances in Visual and Experiential Computing (VEC) will enable capability, adaptability, scalability, and usability that will far exceed the simple information systems of today. VEC technology will transform the way people interact with visual information through, for example, the realization of new mobile and wearable devices and the emergence of autonomous machines and semantically aware spaces. VEC research will drive innovation and competition in many industrial sectors as well as enhance the quality of life for ordinary people. Fast growing visual data has become a bottleneck in human decision processes in several emergent situations. New VEC technology is crucial to extracting information from complex visual and related data sets, combining this information with intuitive modes of human perception, and generating actionable information. The goal of this joint solicitation between NSF and Intel is to foster novel, transformative, multidisciplinary approaches that promote research in VEC technologies, taking into consideration the various challenges present in this field. This solicitation aims to foster a research community committed to advancing research and education at the confluence of VEC technologies, and to transitioning its findings into practice. NSF and Intel will support three types of projects, each three years in duration: Small projects with funding from $500,000 to $1,000,000 per project; Medium projects with funding from $1,000,001 to $2,000,000 per project; and Large projects with funding from $2,000,001 to $3,000,000.?? It is intended that NSF and Intel will cofund each project in equal amounts. This NSF/Intel partnership combines CISE??s experience

The scope is science and technology development, experimentation, and demonstration in the areas of improving and personalizing individual, team, and larger instructional training methods to include the following: - Competency definition and requirements analysis - Measuring, diagnosing, and modeling human expertise and performance - Rapid development of models of human cognition - Specifying and validating, both empirically and practically, new classes of synthetic, computer-generated agents and teammates - Training and rehearsal strategies and models - Environments that support learning and proficiency achievement and sustainment during non-practice or under novel contexts

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) applied 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, 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 the algorithmic contributions and resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

With this Dear Colleague letter (DCL), the NSF is announcing its intention to accept EArly-Concept Grants for Exploratory Research (EAGER) proposals to support NSF researchers in participating in the NIST GCTC teams, with the goal of pursuing novel research on effective integration of networked computer systems and physical devices that will have significant impact in meeting the challenges of the smart city. Priority will be given to researchers who have previously received funding from CPS, or who have related projects from other NSF programs (e.g., Computer Systems Research (CSR), Energy, Power, Control and Networks (EPCN), Secure and Trustworthy Cyberspace (SaTC), including CAREER awardees), and who are members of, or are seeking to, establish GCTC teams building upon the results of NSF-funded projects.

With this Dear Colleague letter (DCL), the NSF is announcing its intention to accept EArly-Concept Grants for Exploratory Research (EAGER) proposals to support NSF researchers in participating in the NIST GCTC teams, with the goal of pursuing novel research on effective integration of networked computer systems and physical devices that will have significant impact in meeting the challenges of the smart city. Priority will be given to researchers who have previously received funding from CPS, or who have related projects from other NSF programs (e.g., Computer Systems Research (CSR), Energy, Power, Control and Networks (EPCN), Secure and Trustworthy Cyberspace (SaTC), including CAREER awardees), and who are members of, or are seeking to, establish GCTC teams building upon the results of NSF-funded projects.

NSF is interested in supporting activities by the NSF Cyberinfrastructure community in the analysis of existing benchmarks, and in the development of new benchmarks, that measure real-world performance and effectiveness of large-scale computing systems for science and engineering discovery. Research, development, and use of performance benchmarks in high-performance computing (HPC) has been active for over 20 years, as evidenced by the development of LINPACK and the emergence of the TOP500 list in the early 1990s, followed by the development of the HPC Challenge Benchmark and the current HPCG effort (http://tiny.cc/hpcg). There have been efforts to provide benchmarks that include real applications, such as the SPEC High Performance Computing Benchmarks (http://spec.org/benchmarks.html#hpg), the Blue Waters SPP suite (http://www.ncsa.illinois.edu/assets/pdf/news/BW1year_apps.pdf), and the NERSC SSP (https://www.nersc.gov/users/computational-systems/nersc-8-system-cori/nersc-8-procurement/trinity-nersc-8-rfp/nersc-8-trinity-benchmarks/ssp/). Recent efforts have sought to broaden the set of relevant benchmarks to more effectively cover performance under different application environments such as data-intensive analysis (e.g., Graph500). Energy efficiency has also emerged in recent years as a relevant and increasingly important area of measurement and profiling for HPC systems (e.g., Green500). In addition to HPC, the Big Data community has gained interest in benchmarking; reference approaches to measuring and characterizing system performance for large-scale data analysis hardware and software systems remains an area of research, development, and community discussion (e.g., on the Big Data Top 100). Industry and academe have convened an ongoing series of workshops and meetings on the topic of Big Data benchmarking (http://clds.ucsd.edu/bdbc/workshops). Given the emergence of inference-based computing, the growing role of data analysis, changes in scientific workflow du

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 arrays, and other critical infrastructure connected by high-speed networking. This complex, distributed, interconnected global cyberinfrastructure ecosystem presents unique cybersecurity challenges. NSF-funded scientific instruments 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. Therefore, an increasing area of focus for NSF is the development and deployment of hardware and software technologies and techniques to protect research cyberinfrastructure across every stage of the scientific workflow.

SoftwareInfrastructure for Sustained Innovation (SI2) is a long-term investment focused on realizing a portion of the Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504730) vision and catalyzing new thinking, paradigms and practices in science and engineering. CIF21 envisions a linked cyberinfrastructure architecture that integrates large-scale computing, high-speed networks, massive data archives, instruments and major facilities, observatories, experiments, and embedded sensors and actuators, across the nation and the world, and that enables research at unprecedented scales, complexity, resolution, and accuracy by integrating computation, data, and experiments in novel ways. Software is a primary modality through which CIF21 innovation and discovery will be realized. It permeates all aspects and layers of cyberinfrastructure (from application codes and frameworks, programming systems, libraries and system software, to middleware, operating systems, networking and the low-level drivers). The CIF21 software infrastructure must address the complexity of this cyberinfrastructure, accommodating: disruptive hardware trends; ever-increasing data volumes; data integrity, privacy, and confidentiality; security; complex application structures and behaviors; and emerging concerns such as fault-tolerance and energy efficiency. The programs must focus on building robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery.
 The Division of Advanced Cyberinfrastructure in the Computer & Information Science & Engineering Directorate (CISE/ACI) is partnering with Directorates and Offices across the NSF to support SI2, a long-term comprehensive program focused on realizing a sustained software infrastructure that is an integral part of CIF21.

Researchers in all fields of science and engineering are being challenged in two key directions.  The first challenge is to push beyond the current boundaries of knowledge to provide ever-deeper insights through fundamental disciplinary research by addressing increasingly complex questions, which often requires extremely sophisticated integration of theoretical, experimental, observational and simulation and modeling results.   These efforts, which have relied heavily on observing platforms and other data collection efforts, computing facilities, software, advanced networking, analytics, visualization and models have led to important breakthroughs in all areas of science and engineering and represent a very strong bottom-up approach to the necessary research infrastructure.  The second, and more extensive challenge, is to synthesize these fundamental ground breaking efforts across multiple fields to transform scientific research into an endeavor that integrates the deep knowledge and research capabilities developed within the universities, industry and government labs. Individuals, teams and communities need to be able work together; likewise, instruments, facilities (including MREFCs), datasets, and cyber-services must be integrated from the group to campus to national scale. One can imagine secure, geographically distributed infrastructure components including advanced computing facilities, scientific instruments, software environments, advanced networks, data storage capabilities, and the critically important human capital and expertise. Greater understanding is also needed of how scientific and research communities will evolve in the presence of new cyberinfrastructure. 

MGI recognizes the importance of materials science to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." DMREF integrates materials discovery, development, property optimization, and systems design and optimization, with each employing a toolset to be developed within a materials innovation infrastructure. The toolset will synergistically integrate advanced computational methods and visual analytics with data-enabled scientific discovery and innovative experimental techniques to revolutionize our approach to materials science and engineering.

The Division of Environmental Biology (DEB) supports fundamental research on populations, species, communities, and ecosystems. Scientific emphases range across many evolutionary and ecological patterns and processes at all spatial and temporal scales. Areas of research include biodiversity, phylogenetic systematics, molecular evolution, life history evolution, natural selection, ecology, biogeography, ecosystem structure, function and services, conservation biology, global change, and biogeochemical cycles. Research on organismal origins, functions, relationships, interactions, and evolutionary history may incorporate field, laboratory, or collection-based approaches; observational or manipulative experiments; synthesis activities; as well as theoretical approaches involving analytical, statistical, or computational modeling.

The Office of Science (SC) of the Department of Energy hereby announces its continuing interest in receiving grant applications for support of work in the following program areas: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, and Nuclear Physics

This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21^st-century challenges.

MGI recognizes the importance of materials science to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." DMREF integrates materials discovery, development, property optimization, and systems design and optimization, with each employing a toolset to be developed within a materials innovation infrastructure. The toolset will synergistically integrate advanced computational methods and visual analytics with data-enabled scientific discovery and innovative experimental techniques to revolutionize our approach to materials science and engineering.

DARPA is soliciting research proposals to develop novel technologies for infrared sensors. The WIRED program seeks to provide high-performance, low-cost infrared imagers that respond in the short wave infrared (SWIR) and mid wave infrared (MWIR), and that can be fabricated directly on silicon-based readout integrated circuit (ROIC) substrates at the wafer scale. Also of interest are innovative approaches to high temperature long wave infrared (LWIR) detectors that directly measure photocurrent.

Help create a sustainable, competitive, and healthy US food system. Use USDA data to create working, interactive applications to get farmers the information they need - and help feed America. What to Create: Submit a working, interactive application that integrates one or more of the required USDA datasets.  Static data visualizations will not be eligible. Applications must include interactive functionality (e.g. the user can change parameters to update the visualization and/or result). Eligible Platforms: Smartphone or tablet (iOS, Android, Blackberry, Kindle, Windows 8 Mobile) Web (mobile or desktop) Desktop (Windows PC, Mac Desktop) Software running on other publicly available hardware (including, but not exclusive to, wearable technology, open source hardware, etc.) Supplemental Material: You must submit a demo video (hosted on YouTube, Vimeo, or Youku) that walks through the main functionality of the application via screencast or video. You must also submit a text description and at least one image/screenshot of your working application. Testing: You must make your app available for testing by providing a link to access your installation file, an uploaded installation file, a beta distribution build, etc. See full testing access options. New & Existing Solutions: Apps may be newly created or pre-existing. If the submitted app existed prior to the competition's submission start date, it must have been updated to integrate the required USDA data during the submission period.

The University of Chicago is offering talented individuals from traditionally underrepresented populations an expenses-paid opportunity to explore graduate education at the University of Chicago. Join us for a weekend of graduate admissions workshops, presentations by world-renowned faculty and their graduate students, and informal socials. Receive advice on submitting a competitive application to graduate programs and learn how to develop your own career as a scientist, academic, or professional.

The Square Kilometre Array, in conjunction with Amazon Web Services (AWS), is pleased to issue this call for proposals for grants to use AWS for radio astronomy data reduction or tools and techniques development.  AWS has made a significant tranche of AWS Services credits available each year, for two years for this purpose, and will host up to 1 Petabyte of radio astronomy datasets as a public resource open to grant recipients and the community in general.

The HHPR Summit is an international meeting supporting human systems research held in Dayton, Ohio with the objective of linking defense and academic research to the commercial domains. The Summit is a forum to generate research knowledge and ideas, recruit and retain key organizations and researchers in the human systems domain, and link research to entrepreneurial outcomes, and diffuse information.

This program provides fellowships, through academic departments and programs of IHEs, to assist graduate students with excellent records who demonstrate financial need and plan to pursue the highest degree available in their course study at the institution in a field designated as an area of national need.