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The Statistics Program supports research in statistical theory and methods, including research in statistical methods for applications to any domain of science and engineering. The theory forms the base for statistical science. The methods are used for stochastic modeling, and the collection, analysis and interpretation of data. The methods characterize uncertainty in the data and facilitate advancement in science and engineering. The Program encourages proposals ranging from single-investigator projects to interdisciplinary team projects.

The goal of the interagency Smartand Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information scienceand engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral 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 multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population.Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

Effective solutions will bring together cyberinfrastructure expertise and domain researchers, to ensure that the resulting cyberinfrastructure address researchers' data needs. The activities should address the data challenges arising in a disciplinary or cross-disciplinary context. (Throughout this solicitation, 'community' refers to a group of researchers interested in solving one or more linked scientific questions, while 'domains' and 'disciplines' refer to areas of expertise or application.) The projects should stimulate data-driven scientific discoveries and innovations, and address broad community needs, nationally and internationally.

Effective solutions will bring together cyberinfrastructure expertise and domain researchers, to ensure that the resulting cyberinfrastructure address researchers' data needs. The activities should address the data challenges arising in a disciplinary or cross-disciplinary context. (Throughout this solicitation, 'community' refers to a group of researchers interested in solving one or more linked scientific questions, while 'domains' and 'disciplines' refer to areas of expertise or application.) The projects should stimulate data-driven scientific discoveries and innovations, and address broad community needs, nationally and internationally.

The National Science Foundation (NSF) through its Divisions of Electrical, Communications and Cyber Systems (ECCS); Chemical, Bioengineering, Environmental and Transport Systems (CBET); Civil, Mechanical and Manufacturing Innovation (CMMI); Information and Intelligent Systems (IIS); and Mathematical Sciences (DMS) announces a solicitation on Multimodal Sensor Systems for Precision Health enabled by Data Harnessing, Artificial Intelligence (AI), and Learning. Next-generation multimodal sensor systems for precision health integrated with AI, machine learning (ML), and mathematical and statistical (MS) methods for learning can be envisioned for harnessing a large volume of diverse data in real time with high accuracy, sensitivity and selectivity, and for building predictive models to enable more precise diagnosis and individualized treatments. It is expected that these multimodal sensor systems will have the potential to identify with high confidence combinations of biomarkers, including kinematic and kinetic indicators associated with specific disease and disability. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts, innovative methodologies, theory, algorithms, and enabling technologies that will address the fundamental scientific issues and technological challenges associated with precision health.

The Hazard Mitigation and Structural Engineering (HMSE) program supports fundamental research to mitigate impacts of natural and anthropogenic hazards on civil infrastructure and to advance the reliability, resiliency, and sustainability of buildings and other structures. Hazards considered within the program include earthquake, tsunami, hurricane, tornado and other loads, as well as explosive and impact loading. Resiliency of buildings and other structures include structural and non-structural systems that, in totality, permit continued occupation or operation in case of an impact by a hazard. Research is encouraged that integrates structural and architectural engineering advances with discoveries in other science and engineering fields, such as earth and atmospheric sciences, material science, mechanics of materials, sensor technology, high performance computational modeling and simulation, dynamic system and control, and economics. The program seeks to fund transformative and cost-effective innovations for hazard mitigation of both new and rehabilitated buildings and other structures. Research in structural and architectural engineering is encouraged that extends beyond mature or current construction materials into investigations of smart and sustainable materials and technologies, and considers the structures in their entirety. In addition, the program funds research on structural health monitoring that goes beyond data acquisition to include the holistic system, integrating condition assessment and decision making tools to improve structural performance.

The National Science Foundation (NSF) seeks new proposals and supplemental funding requests to existing awards that support flexible personalized learning to prepare the science, technology, engineering and mathematics (STEM) workforce of the future. NSF envisions projects that collectively apply to all learners, from young children to those already in the workforce. In particular, we would like to support research that complements an anticipated future funding opportunity made possible by a gift from the Boeing Corporation, which was announced on September 24, 2018 (https://www.nsf.gov/news/news_summ.jsp?cntn_id=296700). The Boeing gift established a partnership between NSF and Boeing to accelerate training in crucial skill areas for the future U.S. workforce. It will be used to support design, development, implementation, and analysis of online courses in model-based engineering, model-based systems engineering, mechatronics, robotics, data science and sensor analytics, program management, and artificial intelligence. These courses will use personalized learning systems to maximize their effectiveness for diverse learners.

The National Science Foundation (NSF) and The Boeing Company are supporting a new initiative, managed and administered by NSF through its EHR Core Research (ECR) program, to accelerate training in critical skill areas for the Nation's engineering and advanced manufacturing workforce. The EHR Core Research: Production Engineering Education and Research (ECR: PEER) initiative supports foundational research arising from the design, development, and deployment of creative online curricula that provide learners at various levels with skills in five focal areas: model-based systems engineering, software engineering, mechatronics, data science, and artificial intelligence. ECR: PEER invites proposals to design, develop, deploy, and study the effectiveness of online courses in any one of these focal areas using the theories and tools of the learning sciences. Proposals for these ECR: PEER Course, Curriculum, and Evaluation projects may request a maximum of $2,000,000 support for a duration of up to three years. Additionally, ECR: PEER welcomes proposals to convene experts in the academic, for-profit, and non-profit sectors to imagine the future of production engineering education for one of the five focal areas. Proposals for these ECR: PEER Workforce Development Workshops may request a maximum of $100,000 support for a duration of up to one year.

A vigorous Mid-Scale Innovations Program (MSIP) was recommended by the 2010 Astronomy and Astrophysics Decadal Survey, citing "many highly promising projects for achieving diverse and timely science." As described in this solicitation, the Division of Astronomical Sciences has established a mid-scale program to support a variety of astronomical activities within a cost range up to $30M. This program will be formally divided into four subcategories: 1) limited term, self-contained science projects; 2) longer term mid-scale facilities; 3) development investments for future mid-scale and large-scale projects; and 4) community open access capabilities. The MSIP will emphasize both strong scientific merit and a well-developed plan for student training and involvement of a diverse workforce in instrumentation, facility development, or data management.

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. Consistent with theMGI Strategic Plan, DMREFhighlights four sets of goals: · Leading a culture shift in materials science and engineering research to encourage and facilitate an integrated team approach; · Integrating experimentation, computation, and theory and equipping the materials scienceand engineering communities with advanced tools and techniques; · Making digital data accessible, findable,and useful to the community; and · Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry. Accordingly, DMREF will support activities that significantly accelerate materials discovery and/or development by building the fundamental knowledge base needed to design and make materials and/or devices with specific and desired functions or properties.

Future ultra-low-energy computing, storage and signal-processing systems can be built on principles derived from organic systems that are at the intersection of chemistry, biology, and engineering. New information technologies can be envisioned that are based on biological principles and that use biomaterials in the fabrication of devices and components; it is anticipated that these information technologies could enable stored data to be retained for more than 100 years and storage capacity to be 1,000 times greater than current capabilities. These could also facilitate compact computers that will operate with substantially lower power than today's computers. Research in support of these goals can have a significant impact on advanced information processing and storage technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, engineering, physics, chemistry, materials science, computer science, and information science that will enable heretofore-unanticipated breakthroughs as well as meet educational goals.

Biological and Environmental Research (BER) of the Office of Science (SC), U.S. Department of Energy (DOE) hereby announces its interest in receiving applications for research of interest to the Genomic Science Program (http://genomicscience.energy.gov) in the following research areas: a) Integrating large-scale systems biology data to model, design, and engineer microbial systems for the production of biofuels and bioproducts: Interdisciplinary approaches to develop innovative, high-throughput modeling, genome-wide design and editing, and engineering technologies for a broad range of microbes relevant for the production of biofuels and bioproducts from biomass. b) Plant systems design for bioenergy: To develop novel technologies for genome-scale engineering to re-design bioenergy crops that can grow in marginal environments while producing high yield of biomass that can be easily converted to biofuels and bioproducts. Applications should include strategies to address biocontainment, minimizing risks of potential release of engineered organisms into the environment or other unintended outcomes.

Biological and Environmental Research (BER) of the Office of Science (SC), U.S. Department of Energy (DOE) hereby announces its interest in receiving applications for research of interest to the Genomic Science Program (http://genomicscience.energy.gov) in the following research areas: a) Integrating large-scale systems biology data to model, design, and engineer microbial systems for the production of biofuels and bioproducts: Interdisciplinary approaches to develop innovative, high-throughput modeling, genome-wide design and editing, and engineering technologies for a broad range of microbes relevant for the production of biofuels and bioproducts from biomass. b) Plant systems design for bioenergy: To develop novel technologies for genome-scale engineering to re-design bioenergy crops that can grow in marginal environments while producing high yield of biomass that can be easily converted to biofuels and bioproducts. Applications should include strategies to address biocontainment, minimizing risks of potential release of engineered organisms into the environment or other unintended outcomes.

The proliferation of mobile and Internet-of-Things (IoT) devices, and their pervasiveness across nearly every sphere of our society, continues to raise questions about the architectures that organize tomorrow's compute infrastructure. At the heart of this trend is the data that will be generated as myriad devices and application services operate simultaneously to digitize a complex domain like a smart building or smart industrial facility. A key shift is from edge devices consuming data produced in the cloud to edge devices being a voluminous producer of data. This shift reopens a broad variety of system-level research questions concerning data placement, movement, processing and sharing. Importantly, the shift also opens the door to compelling new applications with significant industrial and societal impact in domains such as healthcare, manufacturing, transportation, public safety, energy, buildings, and telecommunications.

This program seeks to prepare, nurture, and grow the national scientific research workforce for creating, utilizing, and supporting advanced cyberinfrastructure (CI) to enable and potentially transform fundamental science and engineering research and contribute to the Nation's overall economic competitiveness and security. The goals of this solicitation are to (i) ensure broad adoption of CI tools, methods, and resources by the research community in order to catalyze major research advances and to enhance researchers' abilities to lead the development of new CI; and (ii) integrate core literacy and discipline-appropriate advanced skills in advanced CI as well as computational and data-driven science and engineering into the Nation's educational curriculum/instructional material fabric spanning undergraduate and graduate courses for advancing fundamental research. Pilot and Implementation projects may target one or both of the solicitation goals, while Large-scale Project Conceptualization projects must address both goals. For the purpose of this solicitation, advanced CI is broadly defined as the set of resources, tools, methods, and services for advanced computation, large-scale data handling and analytics, and networking and security for large-scale systems that collectively enable potentially transformative fundamental research.

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.

The Naval Facilities Command, through the Living Marine Resources applied science program (LMR), is soliciting pre-proposals for efforts related to any one of the six (6) themes listed below.  1. Data and Tools for the Assessment and Mitigation of Effects from Construction Noise (LMR N-0001-13).  2. Passive Acoustic Monitoring (PAM) Technology Demonstrations (LMR N-0006-13). 3. Behavioral Responses to Navy Sound Sources (LMR N-0011-13).  4. Hearing and Auditory System Information for Hearing-Based Risk Criteria (N-0012-13).  5. Demonstration and Evaluation of Platform-Independent Improvements to Automated Signal Processing of Passive Acoustic Monitoring (PAM) Data (LMR N0020-13).  6. Capability Development for Hearing Data Collection (LMR N0029-13).

DMREF will support activities that significantly accelerate materials discovery and development by building the fundamental knowledge base needed to advance the design and development of materials with desirable properties or functionality. This will be accomplished through forming interdisciplinary teams of researchers working synergistically in a "closed loop" fashion, building a vibrant research community, leveraging data science, providing ready access to materials data, and educating the future MGI workforce. Achieving this goal could involve some combination of: strategies to advance materials design through testing methodology; theory, modeling, and simulation to predict behavior or assist in analysis of multidimensional input data; and validation through synthesis, growth, processing, characterization, and/or device demonstration.

Advanced computational infrastructure and the ability to perform large-scale simulations and accumulate massive amounts of data have revolutionized scientific and engineering disciplines.  The goal of the CDS&E program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data analysis approaches.  The intellectual drivers may be in an individual discipline or they may cut across more than one discipline in various Directorates.  The key identifying factor is that the outcome relies on the development, adaptation, and utilization of one or more of the capabilities offered by advancement of both research and infrastructure in computation and data, either through cross-cutting or disciplinary programs. 

Every year, Adobe funds a university faculty research program to promote the understanding and use of data science in the area of marketing. Our goal is to encourage both theoretical and empirical development of solutions to problems in marketing. We are open to releasing anonymous data based on proposed research needs if we think the research can benefit from the data. Adobe will provide funding support of up to US$50,000 to a North American academic institution, college, or university for each selected research proposal. Awards will be in the form of an unrestricted gift to the academic institution under the names of the researchers who submitted the proposal.

Over the years, NASA has invested heavily in the development and execution of an extensive array of space astrophysics missions. The magnitude and scope of the archival data from those missions enables science that transcends traditional wavelength regimes and allows researchers to answer questions that would be difficult, if not impossible, to address through an individual observing program. To capitalize on this invaluable asset and enhance the scientific return on NASA mission investments, the Astrophysics Data Analysis Program (ADAP) provides support for investigations whose focus is on the analysis of archival data from NASA space astrophysics missions.

The Science of Learning program supports potentially transformative basic research to advance the science of learning. The goals of the SL Program are to develop basic theoretical insights and fundamental knowledge about learning principles, processes and constraints. Projects that are integrative and/or interdisciplinary may be especially valuable in moving basic understanding of learning forward but research with a single discipline or methodology is also appropriate if it addresses basic scientific questions in learning.   The possibility of developing connections between proposed research and specific scientific, technological, educational, and workforce challenges will be considered as valuable broader impacts, but are not necessarily central to the intellectual merit of proposed research. The program will support  research addressing learning in a wide range of domains at one or more levels of analysis including: molecular/cellular mechanisms; brain systems; cognitive affective, and behavioral processes; and social/cultural influences. The program supports a variety of methods including: experiments, field studies, surveys, secondary-data analyses, and modeling.