Group items tagged

The intersection of justice and community-based health systems is a critical target for addressing the opioid crisis. The National Institute on Drug Abuse intends to establish the Justice Community Opioid Innovation Network (JCOIN) using the cooperative agreement mechanism. The purpose of the network is to establish a national consortium of investigators examining promising interventions and other approaches that can improve the capacity of the justice system to effectively respond to the opioid epidemic. The structure of the network shall consist of three highly integrated components - (1) Clinical Research Centers (each center will propose a study to be executed in at least 5 research performance sites), (2) a single, central Coordination and Translation Center, and (3) a single, central Methodology and Advanced Analytics Resource Center. This FOA solicits applications for Clinical Research Centers. This FOA runs in parallel with companion FOAs that seek applications for a single Coordination and Translation Center (RFA-DA-19-024), and a single Methodology and Advanced Analytics Resource Center (RFA-DA-19-023).

The Science of Science & Innovation Policy (SciSIP) program supports research designed to advance the scientific basis of science and innovation policy. Research funded by the program thus develops, improves and expands models, analytical tools, data and metrics that can be applied in the science policy decision making process. For example, research proposals may develop behavioral and analytical conceptualizations, frameworks or models that have applications across a broad array of SciSIP challenges, including the relationship between broader participation and innovation or creativity. Proposals may also develop methodologies to analyze science and technology data, and to convey the information to a variety of audiences. Researchers are also encouraged to create or improve science and engineering data, metrics and indicators reflecting current discovery, particularly proposals that demonstrate the viability of collecting and analyzing data on knowledge generation and innovation in organizations. Among the many research topics supported are:examinations of the ways in which the contexts, structures and processes of science and engineering research are affected by policy decision, the evaluation of the tangible and intangible returns from investments in science and from investments in research and development, the study of structures and processes that facilitate the development of usable knowledge, theories of creative processes and their transformation into social and economic outcomes, the collection, analysis and visualization of new data describing the scientific and engineering enterprise. The SciSIP program invites the participation of researchers from all of the social, behavioral and economic sciences as well as those working in domain-specific applications such as chemistry, biology, physics, or nanotechnology. The program welcomes proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, conferences, wo

The National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation (NSF) is one of the thirteen principal federal statistical agencies within the United States. It is responsible for the collection, acquisition, analysis, reporting and dissemination of objective, statistical data related to the science and engineering enterprise in the United States and other nations that is relevant and useful to practitioners, researchers, policymakers and the public. NCSES uses this information to prepare a number of statistical data reports as well as analytical reports including the National Science Board's biennial report, Science and Engineering (S&E) Indicators, and Women, Minorities and Persons with Disabilities in Science and Engineering. The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise, to develop improved survey methodologies for NCSES surveys, to create and improve indicators of S&T activities and resources, and strengthen methodologies to analyze and disseminate S&T statistical data. To that end, NCSES invites proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, workshops, experimental research, survey research and data collection and dissemination projects under its program for Research on the Science and Technology Enterprise: Statistics and Surveys.

The NIEHS is establishing an infrastructure, the Human Health Exposure Analysis Resource (HHEAR) as a continuation of the Children's Health Exposure Analysis Resource (CHEAR). The goal of this consortium is to provide the research community access to laboratory and statistical analyses to add or expand the inclusion of environmental exposures in their research and to make that data publicly available as a means to improve our knowledge of the comprehensive effects of environmental exposures on human health throughout the life course. This FOA solicits Laboratories (Lab Hubs) providing a comprehensive suite of analysis of environmental exposures in samples such as dust, soil, and drinking water related to the immediate environment of individuals and linked to health endpoints. Each Hub will incorporate a developmental core to develop novel measures for environmental samples, expanding the number of current, commonly measured analytes, and developing new methods for detecting analytes in other environmental samples and providing additional insight into the sources of exposures that influence human health. The Environmental Monitoring Lab will also serve as a 'clearinghouse for evaluation and provision of emerging tools and technologies for personal exposure assessment to the client community.

 The purpose of this Funding Opportunity Announcement (FOA) is to develop advanced analytical models, tools and metrics to enhance the decision making and professional evaluation in life sciences management and administration. It is envisioned that the developed tools will be used by the NGOs/disease foundations, advocacy groups, publishing industry, research funders, policy makers and academic institutions.

The purpose of this Funding Opportunity Announcement (FOA) is to develop advanced analytical models, tools and metrics to enhance the decision making and professional evaluation in life sciences management and administration. It is envisioned that the developed tools will be used by the NGOs/disease foundations, advocacy groups, publishing industry, research funders, policy makers and academic institutions.

As part of NSF's Harnessing the Data Revolution (HDR), the Directorate for Social, Behavioral and Economic Sciences (SBE) seeks to develop user-friendly large-scale next-generation data resources and relevant analytic techniques to advance fundamental research in SBE areas of study. Successful proposals will, within the financial resources provided by the award, construct such databases and/or relevant analytic techniques and produce a finished product that will enable new types of data-intensive research. The databases or techniques should have significant impacts, either across multiple fields or within broad disciplinary areas, by enabling new types of data-intensive research in the SBE sciences.

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) other computing and information 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, artificial intelligence and its applications, 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 both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

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) other computing and information 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, artificial intelligence and its applications, 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 both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering 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." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering 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." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

The Bureau of Justice Statistics (BJS) Federal Justice Statistics Program (FJSP) collects, standardizes, and publishes statistics about the federal response to crime and the operation of the federal criminal justice system. The FJSP produces annual standardized data files (Standard Analysis Files, or SAFs), which document the federal criminal case processing stages from arrest, to prosecution, pretrial release, adjudication, sentencing, appeals, and corrections. BJS seeks an agent to implement the Federal Justice Statistics Analytical Support Program (FJSASP) project. This project is designed to provide scientific and technical support to BJS for methodological research, statistical analysis, and the generation of statistical reports using data from the FJSP. In addition, the FJSASP will work with BJS to identify additional sources of data to further enhance the FJSP (e.g., immigration enforcement and court statistics; enforcement data from federal regulatory agencies; civil data from the federal courts; and staffing and budget statistics).

This Funding Opportunity Announcement (FOA) aims to stimulate the integration of data across HIV research networks and cohorts as well as the development, adaptation and application of state-of-the-art analytic methods to achieve a better understanding of the various factors that characterize neurobehavioral and psychosocial functioning of people living with HIV or those at risk for HIV.

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) other computing and information 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, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices.

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) other computing and information 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, artificial intelligence and its applications, 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 both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

AAAS offers fellowships in nine programmatic areas. Specific host offices and assignments vary from year to year. Congressional Diplomacy, Security& Development Energy, Environment & Agriculture Health, Education & Human Services Big Data & Analytics Judicial Branch Roger Revelle Fellowship in Global Stewardship AAAS Overseas Fellowships at USAID Missions (limited eligibility) Global Health & Development Fellowships (limited eligibility)

The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets.  NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise, to develop improved survey methodologies for NCSES surveys, to create and improve indicators of S&T activities and resources, and strengthen methodologies to analyze and disseminate S&T statistical data. To that end, NCSES invites proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, workshops, experimental research, survey research and data collection and dissemination projects under its program for Research on the Science and Technology Enterprise:  Statistics and Surveys.

This Funding Opportunity Announcement (FOA) encourages the submission of investigator-initiated research grant applications to support the secondary analysis of existing data sets with the goal of enhancing our understanding of patterns of alcohol consumption and the epidemiology of alcohol-related problems. Research grants for the Secondary Analysis of Existing Alcohol Epidemiology Data Sets are intended to provide support for studies that utilize currently available data sets to increase our understanding of the incidence, prevalence and etiology of alcohol related problems and disorders in the population, as well as the risk and protective factors associated with them. Research that employs analytic techniques which demonstrate or promote methodological advances in alcohol-related epidemiologic research is also of interest.

This program supports theoretical and computational materials research and education in the topical areas represented in DMR programs, including condensed matter physics, polymers, solid-state and materials chemistry, metals and nanostructures, electronic and photonic materials, ceramics, and biomaterials. The program supports fundamental research that advances conceptual, analytical, and computational techniques for materials research. A broad spectrum of research is supported using electronic structure methods, many-body theory, statistical mechanics, and Monte Carlo and molecular dynamics simulations, along with other techniques, many involving advanced 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 and to reveal new materials phenomena. Areas of recent interest include, but are not limited to: strongly correlated electron systems; low-dimensional systems; nonequilibrium phenomena, including pattern formation, microstructural evolution, and fracture; high-temperature superconductivity; nanostructured materials and mesoscale phenomena; quantum coherence and its control; and soft condensed matter, including systems of biological interest.

The Sensors, Dynamics, and Control (SDC) program supports fundamental research on the analysis, measurement, monitoring and control of complex dynamical and structural systems, including development of new analytical, computational and experimental tools, and novel applications to engineered and natural systems. Program objectives are the discovery of new phenomena and the investigation of innovative methods and applications for dynamics, measurement, and control. Transformative research on complex networks, linear and nonlinear discrete or infinite dimensional systems spanning a multitude of time and length scales and physical domains are of interest, as are highly interdisciplinary projects and projects addressing security, resilience and sustainability. Basic research strongly motivated by industry needs or other real-life applications is welcome.The SDC program supports fundamental research on the theories of dynamical systems to uncover novel paradigms for modeling, control and analysis of dynamic phenomena and systems that undergo spatial and temporal evolution with applications crossing interdisciplinary boundaries, along with fundamental studies on stability, phase transitions, and wave propagation in complex and non-local media. Furthermore, the program supports fundamental research on monitoring, analysis, and decision-making processes for integrity monitoring, sensors reliability and safety of complex engineered systems, especially under conditions of uncertainty. Of interest is the investigation of big data (high-volume and high-speed) issues related to virtually-continuous streams of measurements from heterogeneous sensors for continuous systems monitoring. The SDC program also includes fundamental research on control theory and its applications. Topics of current interest include unconventional applications of control; the combined roles of feedback, feedforward and uncertainty; integrated feedback, communication and signal processing; and control conc

The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise, to develop improved survey methodologies for NCSES surveys, to create and improve indicators of S&T activities and resources, and strengthen methodologies to analyze and disseminate S&T statistical data. To that end, NCSES invites proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, workshops, experimental research, survey research and data collection and dissemination projects under its program for Research on the Science and Technology Enterprise: Statistics and Surveys.

The Office of Advanced Scientific Computing Research (ASCR) in the Office of Science (SC), U.S. Department of Energy (DOE), hereby invites applications for basic research that significantly advances management, analysis and visualization of data in disciplines supported by DOE in the context of emerging architectures for extreme scale computing platforms. The purpose of this announcement is to invite applications for basic computer science research on five major themes: 1. Usability and user interface design; 2. In situ methods for data management, analysis and visualization; 3. Design of in situ workflows to support data management, processing, analysis and visualization; 4. New approaches to scalable interactive visual analytic environments; and/or 5. Proxy applications or workflows and/or simulations for data management, analysis and visualization software to support co-design of extreme scale systems. The supported research will lay the foundation for building the software infrastructure to support scientific data management, analysis and visualization in the context of extreme scale computing.