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Northrop Grumman is seeking advanced algorithms or other computer learning techniques that have the potential to improve future Electronic Warfare (EW) systems. The ambient RF environment experienced by EW systems is filled with signals from a diversity of radiating sources. To an EW system the multitude of signals are effectively summed together and appear to the processor as simultaneous or near simultaneous signals. EW processing consists of routines designed to identify and sort known signals into their constituent parts.

The NIGMS Postdoctoral Research Associate (PRAT) Programs overarching goal is to provide high quality postdoctoral research training in the basic biomedical sciences, in NIH intramural research laboratories, to a diverse group of postdoctoral fellows to prepare them for leadership positions in biomedical careers. The research projects proposed should focus on NIGMS mission-related areas of basic biomedical science. These include cell biology, biophysics, genetics, developmental biology, pharmacology, physiology, biological chemistry, computational biology, technology development and bioinformatics. Studies employing model organisms are encouraged

The DMR Polymers Program supports fundamental research and education on polymeric materials and polymer science. The program portfolio is mainly experimental and highly diverse with components of materials science, chemistry, physics, and other related disciplines.

The overall goal of the Intramural NIGMS Postdoctoral Research Associate (PRAT) program is to help ensure that a diverse pool of highly trained scientists is available in appropriate scientific disciplines to address the Nation's biomedical research needs.

The goal of this program is to detect, prevent, eradicate, and/or control invasive plant species to promote resiliency, watershed stability, and biological diversity on federal, state, or private land.

RWJF is now looking for researchers to study the impact the program has had on the changing face of nursing. Up to four grants of $3,000 each will be awarded to individual researchers for the development of a manuscript in one of the following categories: supports and barriers for accelerated nursing students; characteristics of male nursing students; increasing diversity and cultural climate of nursing schools; student debt and accelerated nursing education: policy implications; and effective mentoring/necessary components.

The goals of the Network for Computational Nanotechnology (NCN) are to: 1) accelerate the transformation of nanoscience to nanotechnology through the integration of simulation with experimentation; 2) engage an ever-larger and more diverse cyber community sharing novel, high-quality nanoscale computation and simulation research and educational resources; 3) develop open-access, open-source software to stimulate data sharing; and 4) inspire and educate the next-generation workforce. The NCN consists of a stand-alone Cyber Platform, which provides computation, simulation, and education services to over 330,000 researchers, educators, students, and industry members of the nanoscience and engineering community annually worldwide; and Nodes, which develop compelling new computational and simulation tools to disseminate through Cyber Platform

The NSF/Intel Partnership on Computer Assisted Programming for Heterogeneous Architectures (CAPA) aims to address the problem of effective software development for diverse hardware architectures through groundbreaking university research that will lead to a significant, measurable leap in software development productivity by partially or fully automating software development tasks that are currently performed by humans. The main research objectives for CAPA include programmer effectiveness, performance portability, and performance predictability. In order to address these objectives, CAPA seeks research proposals that explore (1) programming abstractions and/or methodologies that separate performance-related aspects of program design from how they are implemented; (2) program synthesis and machine learning approaches for automatic software construction that are demonstrably correct; (3) advanced hardware-based cost models and abstractions to support multi-target code generation and performance predictability for specified heterogeneous hardware architectures; and (4) integration of research results into principled software development practices.

Miami faculty should notify Associate Provost Jim Oris of their interest in the following RFP. ---------- CGS invites doctoral-granting member institutions to apply to participate in Understanding PhD Career Pathways for Program Improvement, a multi-institution effort to collect and use data on PhD career pathways, funded by The Andrew W. Mellon Foundation and the National Science Foundation (NSF #1661272). This is an important opportunity to deepen your institution's understanding of the career goals and outcomes of its PhDs; communicate your support for the career diversity of PhDs; make evidence-based interventions that support the success of PhDs and the recruitment of future students; and access anonymized benchmarking data compiled from other project partners.   Awards: Option 1: Humanities Only. Provides awards of $30,000 each to support implementation of surveys of humanities PhD students and alumni over a period of twenty-four months. Supported by the Andrew W. Mellon Foundation; 15 awards available. Please indicate in your proposal why a humanities-only project aligns with your institutional mission.   Option 2: STEM Only. Provides awards of $50,000 to each to support implementation of surveys of STEM PhD students and alumni over a period of thirty-six months. Supported by the National Science Foundation; 15 awards available. Please indicate in your proposal why a STEM-only project aligns with your institutional mission.   Option 3: Combined Proposal. If an institution meets the eligibility requirements for both the Humanities and STEM awards, CGS strongly encourages the submission of a combined proposal. Institutions selected to participate in this category will receive a total award amount of $80,000.

The DoD strives for superiority in a complex operational environment composed of heterogeneous and ever-evolving pieces such as sensors and processing hardware, software, and wired and wireless communications infrastructure. To achieve superiority in this dynamic environment, the DoD invests in fully networked and maximally-capable sensors and platforms at the cutting edge of performance. Software has emerged as a key enabler of capability and flexibility in DoD systems. Software is essential to providing a vast range of military capabilities by playing a fundamental role [1] that deepens, broadens, links, and integrates diverse system elements. A pervasive DoD challenge is the production of software that provides the Warfighter superior and affordable military capability in an environment where hardware and sensor technology is rapidly advancing and systems' performance demands are ever-increasing. The Government Accountability Office has identified the increasing scope of software development as a contributing factor to poor acquisition program outcome [2]. OASD(R&E) has identified the need for advanced software engineering technology to enhance the producibility of software in this environment with the goal of speeding the delivery of affordable capability to the Warfighter and sustaining it.

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 computing research infrastructure. 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. The CRI program supports two classes of awards: Institutional Infrastructure (II) awards support the creation of new (II-New) CISE research infrastructure or the enhancement (II-EN) of existing CISE research infrastructure to enable world-class CISE research opportunities at the awardee and collaborating institutions. Community Infrastructure (CI) awards support the planning (CI-P) for new CISE community research infrastructure, the creation of new (CI-New) CISE research infrastructure or the enhancement (CI-EN) of existing CISE infrastructure to enable world-class CISE research opportunities for broad-based communities of CISE researchers that extend well beyond the awardee institutions. Each CI award may support the operation of such infrastructure, ensuring that the awardee institution(s) is (are) well-positioned to provide a high quality of service to CISE community researchers expected to use the infrastructure to realize their research goals.

The Chemical Theory, Models and Computational Methods program supports the discovery and development of theoretical and computational methods or models to address a range of chemical challenges, with emphasis on emerging areas of chemical research.  Proposals that focus on established theoretical or computational approaches should involve innovative additions or modifications that substantially broaden their applicability.  Areas of interest include, but are not limited to, electronic structure, quantum reaction dynamics, statistical mechanics, molecular dynamics, and simulation and modeling techniques for molecular systems and systems in condensed phases.  Areas of application span the full range of chemical systems from small molecules to mesoscopic aggregates, including single molecules, biological systems and materials in condensed phases.   Despite the diverse application areas, the goal of the program is to support the development of new theoretical and computational methodologies that have the potential of being broadly applicable to a range of challenging chemical problems. We are particularly interested in fundamental areas of chemical research that are difficult or impossible to address using current synthetic, experimental, and/or computational methodologies.  We encourage the integration of innovative software development with methodological and algorithmic development, especially computational approaches that allow efficient utilization of the high end computers of the future.

The CISE Research Infrastructure (CRI) program drives discovery and learning in the computing disciplines by supporting the creation and enhancement of world-class computing research infrastructure. 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 predominately undergraduate institutions, have access to such infrastructure.

 A primary focus is on developing algorithms and prototyping products for combined use of data from Landsat and Sentinel-2toward global land monitoring. However, we also welcome proposals combining Landsat with other sources of moderate resolution data, such as IRS and/or CBERS. Proposals fusing optical sensor data as listed above with radar observations such as from Sentinel-1, as well as those pursuing innovative use of thermal infrared data to improve LCLUC monitoring, are also welcome. The ultimate goal is to develop multisensor methods based on increased temporal-spatial coverage and measurement spectral diversity to advance the virtual constellation paradigm for midresolution land imaging 

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

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 computing research infrastructure. 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. The CRI program supports two classes of awards: Institutional Infrastructure (II) awards support the creation of new (II-New) CISE research infrastructure or the enhancement (II-EN) of existing CISE research infrastructure to enable world-class CISE research opportunities at the awardee and collaborating institutions.   Community Infrastructure (CI) awards support the planning (CI-P) for new CISE community research infrastructure, the creation of new (CI-New) CISE research infrastructure or the enhancement (CI-EN) of existing CISE infrastructure to enable world-class CISE research opportunities for broad-based communities of CISE researchers that extend well beyond the awardee institutions.  Each CI award may support the operation of such infrastructure, ensuring that the awardee institution(s) is (are) well-positioned to provide a high quality of service to CISE community researchers expected to use the infrastructure to realize their research goals.

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 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 NSF Mid-scale Research Infrastructure-2 Program (Mid-scale RI-2) supports implementation of projects that comprise any combination ofequipment, instrumentation, computational hardware and software, and the necessary commissioning and human capital in support of implementation of the same. The total cost for Mid-scale RI-2 projects ranges from $20 million to below the minimum award funded by the Major Research Equipment and Facilities Construction (MREFC) Program, currently $70 million. Mid-scale RI-2 projects will directly enable advances in any of the research domains supported by NSF, including STEM education. Projects may also include upgrades to existing research infrastructure. The Mid-scale RI-2 Program emphasizes strong scientific merit and response to an identified need of the research community, technical and managerial readiness for implementation, and a well-developed plan for student training and involvement of a diverse workforce in mid-scale facility development, and/or associated data management. Mid-scale RI-2 will consider only the implementation (typically construction or acquisition) stage of a project, including a limited degree of advanced development immediately preparatory to implementation. It is thus intended that Mid-scale RI-2 will support projects in high states of readiness for implementation, i.e., those that have already matured through previous developmental investments.

The GO Competition is a series of prize challenges to accelerate the development and comprehensive evaluation of grid software solutions. The first GO Competition, Challenge 1, is an algorithm competition focused on the security-constrained optimal power flow (SCOPF) problem for the electric power sector. Awardees under this FOA will be required to participate in Challenge 1. As described in detail in Appendix A1 to this FOA and on the GO Competition website (https://gocompetition.energy.gov/), Challenge 1 is anticipated to launch in the Fall of 2018. Participation in the GO Competition Challenge 1 will be open to anyone that satisfies the applicable requirements in Rules Document specified on the GO Competition website (https://gocompetition.energy.gov/competition-rules), not just those awarded under ARPA-E DE-FOA-0001952. The purpose of this FOA is to provide grants: (i) to further incentivize and identify innovative research for solution methods applicable to Challenge 1, and (ii) to enable broader diversity in team domain expertise, i.e., to encourage teams to participate that do not traditionally focus on the particular problems that are targeted but otherwise have innovative approaches for this class of mathematical programs. While Challenge 1 focuses on a power systems problem, the Challenge and this FOA target a much broader audience (e.g., those specialized in operations research, applied mathematics, optimization methods and algorithms, controls etc.). Existing grid software was designed for a power grid centered on conventional generation and transmission technologies.