Group items tagged

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.

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.

The goal of the Smart and Connected Health (SCH) Program is to accelerate the development and use of innovative approaches that would support the much needed transformation of healthcare from reactive and hospital-centered to preventive, proactive, evidence-based, person-centered and focused on well-being rather than disease. Approaches that partner technology-based solutions with biobehavioral health research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next generation health care solutions and encourage existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as sensor technology, networking, information and machine learning technology, decision support systems, modeling of behavioral and cognitive processes, as well as system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, social interactions, cognitive limitations, barriers to behavioral change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems. Such solutions demand multidisciplinary teams ready to address technical, behavioral and clinical issues ranging from fundamental science to clinical practice.

The goal of the Smart and Connected Health (SCH) Program is to accelerate the development and use of innovative approaches that would support the much needed transformation of healthcare from reactive and hospital-centered to preventive, proactive, evidence-based, person-centered and focused on well-being rather than disease. Approaches that partner technology-based solutions with biobehavioral health research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next generation health care solutions and encourage existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as sensor technology, networking, information and machine learning technology, decision support systems, modeling of behavioral and cognitive processes, as well as system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, social interactions, cognitive limitations, barriers to behavioral change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems. Such solutions demand multidisciplinary teams ready to address technical, behavioral and clinical issues ranging from fundamental science to clinical practice.

The purpose of this BD2K Funding Opportunity Announcement (FOA) is to support the development, improvement and implementation of tools and approaches that increase the efficiency and effectiveness of digital curation processes used to characterize and describe the digital data used in or resulting from biomedical research.

The purpose of this BD2K Funding Opportunity Announcement (FOA) is to support the development, improvement and implementation of tools and approaches that increase the efficiency and effectiveness of digital curation processes used to characterize and describe the digital data used in or resulting from biomedical research.

The SNM-IS solicitation seeks proposals that investigate novel scalable nanomanufacturing and integration methods for nano-enabled integrated systems with a clear commercial relevance. Proposals should consider addressing key aspects of the nanomanufacturing value chain comprised of nano-scale building-blocks → complex nanomaterials and nanostructures → functional components and devices → integrated sub-systems and systems

The Scalable Parallelism in the Extreme (SPX) program aims to support research addressing the challenges of increasing performance in this modern era of parallel computing. This will require a collaborative effort among researchers in multiple areas, from services and applications down to micro-architecture. SPX encompasses all five NSCI Strategic Objectives, including supporting foundational research toward architecture and software approaches that drive performance improvements in the post-Moore's Law era; development and deployment of programmable, scalable, and reusable platforms in the national HPC and scientific cyberinfrastructure ecosystem; increased coherence of data analytic computing and modeling and simulation; and capable extreme-scale computing. Coordination with industrial efforts that pursue related goals are encouraged.

The Macromolecular, Supramolecular and Nanochemistry (MSN) Program focuses on basic research that addresses fundamental questions regarding the chemistry of macromolecular, supramolecular and nanoscopic species and other organized structures and that advances chemistry knowledge in these areas.  Research of interest to this program will explore novel chemistry concepts in the following topics: (1) The development of novel synthetic approaches to clusters, nanoparticles, polymers, and supramolecular architectures; innovative surface functionalization methodologies; surface monolayer chemistry; and template-directed synthesis.  (2) The study of molecular-scale interactions that give rise to macromolecular, supramolecular or nanoparticulate self-assembly into discrete structures; and the study of chemical forces and dynamics that are responsible for spatial organization in discrete organic, inorganic, or hybrid systems (excluding extended solids).  (3) Investigations that utilize advanced experimental or computational methods to understand or to predict the chemical structure, unique chemical and physicochemical properties, and chemical reactivities that result from the organized or nanoscopic structures.  Research in which theory advances experiment and experiment advances theory synergistically is of special interest.

The Macromolecular, Supramolecular and Nanochemistry (MSN) Program focuses on basic research that addresses fundamental questions regarding the chemistry of macromolecular, supramolecular and nanoscopic species and other organized structures and that advances chemistry knowledge in these areas.  Research of interest to this program will explore novel chemistry concepts in the following topics: (1) The development of novel synthetic approaches to clusters, nanoparticles, polymers, and supramolecular architectures; innovative surface functionalization methodologies; surface monolayer chemistry; and template-directed synthesis.  (2) The study of molecular-scale interactions that give rise to macromolecular, supramolecular or nanoparticulate self-assembly into discrete structures; and the study of chemical forces and dynamics that are responsible for spatial organization in discrete organic, inorganic, or hybrid systems (excluding extended solids).  (3) Investigations that utilize advanced experimental or computational methods to understand or to predict the chemical structure, unique chemical and physicochemical properties, and chemical reactivities that result from the organized or nanoscopic structures.  Research in which theory advances experiment and experiment advances theory synergistically is of special interest.

This FOA invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

This FOA invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

I-Corps@Ohio is a statewide program to assist faculty and graduate students from Ohio universities and colleges to validate the market potential of their technologies and validate and launch startup companies. I-Corps@Ohio is modeled after the National Science Foundation's (NSF) successful I-Corps program, which is proven to increase innovation, entrepreneurship, and industry collaboration. The I-Corps@Ohio program is an initiative of the Ohio Department of Higher Education.

Goals of the Advanced Information Systems Technology program The goals of the Advanced Information Systems Technology (AIST) program are to identify, develop, and demonstrate advanced information system technologies that: ·Reduce the risk, cost, size, and development time for Earth science space-based, airborne, and ground-based information systems, ·Increase the accessibility and utility of science data, and ·Enable new observations and information products.

The Office of Fusion Energy Sciences (FES) and the Office of Advanced Scientific Computing Research (ASCR) of the Office of Science (SC), U.S. Department of Energy (DOE), announce their interest in receiving applications from multi-institutional interdisciplinary teams to establish scientific application partnerships under the SC-wide Scientific Discovery through Advanced Computing (SciDAC) program in the area of integrated simulations for fusion energy sciences. The goal of this announcement is to select applications that can take advantage of today's multi-petascale DOE high-performance computing (DOE HPC) systems to accelerate scientific discovery in strategically important areas of magnetic fusion energy science and address high- priority issues identified in recent community studies. The specific areas of interest under this Funding Opportunity Announcement (FOA) are: 1. Plasma Disruptions in Tokamaks 2. Boundary Physics 3. Plasma-Materials Interactions 4. Whole Device Modeling

The High Priority (HP) Grant Program is a discretionary (i.e., competitive) program which provides financial assistance to: 1)advance the technological capability and promote HP Innovative Technology Deployment (HP-ITD) to include the deployment of intelligent transportation system (i.e., formerly CVISN) applications for commercial motor vehicle (CMV) operations, including CMVs, commercial drivers, and carrier-specific information systems/networks; to support/maintain CMV information systems/networks; to link Federal Motor Carrier Safety Administration (FMCSA) information systems with State CMV information systems; to improve the safety and productivity of CMVs and commercial drivers; to reduce costs associated with CMV operations and Federal and State CMV regulatory requirements; and/or 2)carry out HP-CMV Safety activities and projects that augment motor carrier safety activities and projects planned in accordance with the Motor Carrier Safety Assistance Program (MCSAP) including projects related to Performance and Registration Information Systems Management (PRISM) and Safety Data Quality (SaDIP).

The Smart and Autonomous Systems (S&AS) program focuses on Intelligent Physical Systems (IPS) that are cognizant, taskable, reflective, ethical, and knowledge-rich. The S&AS program welcomes research on IPS that are aware of their capabilities and limitations, leading to long-term autonomy requiring minimal or no human operator intervention. Example IPS include, but are not limited to, robotic platforms and networked systems that combine computing, sensing, communication, and actuation. Cognizant IPS exhibit high-level awareness beyond primitive actions, in support of persistent and long-term autonomy. Taskable IPS can interpret high-level, possibly vague, instructions, translating them into concrete actions that are dependent on the particular context in which the IPS is operating. Reflective IPS can learn from their own experiences and those of other entities, such as other IPS or humans, and from instruction or observation; they may exhibit self-aware and self-optimizing capabilities. Ethical IPS should adhere to a system of societal and legal rules, taking those rules into account when making decisions. Knowledge-rich IPS employ a variety of representation and reasoning mechanisms, such as semantic, probabilistic and commonsense reasoning; are cognitively plausible; reason about uncertainty in decision making; and reason about the intentions of other entities in decision making.

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, and other critical infrastructure connected by high-speed networking. This complex, distributed, interconnected global cyberinfrastructure ecosystem presents unique cybersecurity challenges. NSF-funded scientific instruments, sensors and equipment 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.

The overarching goal of INFEWS is to catalyze well-integrated interdisciplinary and convergent research to transform scientific understanding of the FEW nexus (integrating all three components rather than addressing them separately), in order to improve system function and management, address system stress, increase resilience, and ensure sustainability. The NSF INFEWS initiative is designed specifically to attain the following goals: 1. Significantly advance our understanding of the food-energy-water system through quantitative, predictive and computational modeling, including support for relevant cyberinfrastructure; 2. Develop real-time, cyber-enabled interfaces that improve understanding of the behavior of FEW systems and increase decision support capability; 3. Enable research that will lead to innovative solutions to critical FEW systems problems; and 4. Grow the scientific workforce capable of studying and managing the FEW system, through education and other professional development opportunities.

The National Science Foundation (NSF) seeks to further develop and nurture a national innovation ecosystem that builds upon fundamental research to guide the output of scientific discoveries closer to the development of technologies, products, processes and services that benefit society. The goal of the program is to dramatically reduce the period of time necessary to bring a promising idea from its inception to widespread implementation.

This initiative enables interagency cooperation on one of the most pressing problems of the millennium - understanding interactions across the FEW nexus - how it is likely to affect our world, and how we can proactively plan for its consequences. It allows the partner agencies - National Science Foundation (NSF) and the United States Department of Agriculture National Institute of Food and Agriculture (USDA/NIFA) and others - to combine resources to identify and fund the most meritorious and highest-impact projects that support their respective missions, while eliminating duplication of effort and fostering collaboration between agencies and the investigators they support.

Over the past few years, Project Open Data (https://project-open-data.cio.gov/) has sought to identify and share best practices, examples, and software code to assist federal agencies with opening up access to data. Moreover, there have been efforts to scale up "open data" across various application sectors, including health, energy, climate, education and learning, finance, public safety, and global development, unlocking valuable data and improving decision making by making data resources more open and accessible to innovators and the public. NSF has established a national network of Big Data Regional Innovation Hubs and Spokes (BD Hubs and Spokes), comprising members from academia, industry, and government, with the goal of igniting new public-private partnerships across the Nation in big data research and development as well as training and education. Facilitating access to data is one of the objectives of the BD Hubs and Spokes. Collectively, these initiatives constitute an important first step in supporting the growing and interdisciplinary data science research community, which requires access to real-world datasets, e.g., as training data that can further data science, including machine learning capabilities, and enhance knowledge and decision making in various application sectors.

CAREER: The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation's most prestigious awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organizations. Such activities should build a firm foundation for a lifetime of leadership in integrating education and research. NSF encourages submission of CAREER proposals from junior faculty members at all CAREER-eligible organizations and especially encourages women, members of underrepresented minority groups, and persons with disabilities to apply.

This FOA encourages Research Project Grant (R01) applications for research and development of technologies that monitor health or deliver care in a real-time, accessible, effective, and minimally obtrusive way. These systems are expected to integrate, process, analyze, communicate, and present data so that the individuals are engaged and empowered in their own healthcare with reduced burden to care providers. The development of these technology systems has the potential to significantly improve the quality of life for people with disabilities, people aging with mild impairments, as well as individuals with chronic conditions.