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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 Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; or the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to involve the public health research community, including for example, epidemiologists, physicians, veterinarians, food scientists, social scientists, entomologists, pathologists, virologists, or parasitologists with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The goals of the Program are to: (i) advance knowledge about the processes that force and regulate the atmosphere’s synoptic and planetary circulation, weather and climate, and (ii) sustain the pool of human resources required for excellence in synoptic and global atmospheric dynamics and climate research.Research topics include theoretical, observational and modeling studies of the general circulation of the stratosphere and troposphere; synoptic scale weather phenomena; processes that govern climate; the causes of climate variability and change; methods to predict climate variations; extended weather and climate predictability; development and testing of parameterization of physical processes; numerical methods for use in large-scale weather and climate models; the assembly and analysis of instrumental and/or modeled weather and climate data; data assimilation studies; development and use of climate models to diagnose and simulate climate and its variations and change.Some Climate and Large Scale Dynamics (CLD) proposals address multidisciplinary problems and are often co-reviewed with other NSF programs, some of which, unlike CLD, use panels in addition to mail reviewers, and thus have target dates or deadlines. Proposed research that spans in substantive ways topics appropriate to programs in other divisions at NSF, e.g., ocean sciences, ecological sciences, hydrological sciences, geography and regional sciences, applied math and statistics, etc., must be submitted at times consistent with target dates or deadlines established by those programs. If it's not clear whether your proposed research is appropriate for co-review, please contact CLD staff (listed above) or the potential co-reviewing program staff (including but not limited to)Eric Itsweire (Physical Oceanography), eitsweir@nsf.govL. Douglas James (Hydrological Sciences), ldjames@nsf.govThomas Baerwald (Geography and Regional Sciences), tbaerwal@nsf.govTom Russell (Applied and Computational Math),

The goals of the Program are to: (i) advance knowledge about the processes that force and regulate the atmosphere’s synoptic and planetary circulation, weather and climate, and (ii) sustain the pool of human resources required for excellence in synoptic and global atmospheric dynamics and climate research. Research topics include theoretical, observational and modeling studies of the general circulation of the stratosphere and troposphere; synoptic scale weather phenomena; processes that govern climate; the causes of climate variability and change; methods to predict climate variations; extended weather and climate predictability; development and testing of parameterization of physical processes; numerical methods for use in large-scale weather and climate models; the assembly and analysis of instrumental and/or modeled weather and climate data; data assimilation studies; development and use of climate models to diagnose and simulate climate and its variations and change. Some Climate and Large Scale Dynamics (CLD) proposals address multidisciplinary problems and are often co-reviewed with other NSF programs, some of which, unlike CLD, use panels in addition to mail reviewers, and thus have target dates or deadlines. Proposed research that spans in substantive ways topics appropriate to programs in other divisions at NSF, e.g., ocean sciences, ecological sciences, hydrological sciences, geography and regional sciences, applied math and statistics, etc., must be submitted at times consistent with target dates or deadlines established by those programs. If it's not clear whether your proposed research is appropriate for co-review, please contact CLD staff.

The Fellowship Program expects to award at least three new Ph.D. Fellowships in 2018 to students who are interested in careers related to marine ecosystem and population dynamics, with a focus on modeling and managing systems of living marine resources. The emphasis will be on the development and implementation of quantitative methods for assessing marine ecosystems, for assessing the status of fish, invertebrate, and other targeted species stocks and for assessing the status of marine mammals, seabirds, and other protected species. Fellows will work on thesis problems of public interest and relevance to National Marine Fisheries Service (NMFS) under the guidance of NMFS mentors at participating NMFS Science Centers or Offices. The NMFS-Sea Grant Fellowship in Population and Ecosystem Dynamics meets NOAA's Healthy Oceans goal of "Marine fisheries, habitats, biodiversity sustained with healthy and productive ecosystems".

A. Proposals for the development of novel collaborative perception algorithms that will enable heterogeneous teams of UxS (specifically unmanned air and ground systems) to share knowledge and perform joint target search and tracking autonomously. While existing distributed data fusion methods have looked at probabilistic representations for fusing detections at a decision level, work is needed to investigate shared perceptual features that exist across unmanned air and ground systems to enable the performance of collaborative tasks.  B. Development of a new Rigid Body Dynamics Software Library for Mathematical and Physics-Based Modeling and Simulation. The basic research proposed here would involve the development of a new software library for the temporal (time) integration of the governing equations of rigid body dynamics. The temporal integration technique employed in this new library involves the application of the Runge-Kutta method of various orders and possibly other finite-difference-type techniques to a system of equations consisting of kinematic equations (arising from the Lie Group structure of the group of rotation transformations) which define the first and second time derivatives of the rotation transformation in terms of angular velocity and angular acceleration together with the equations of motion (balance of momentum and balance of angular momentum) of a rigid body. C. Robustness of the Use of Botanical DNA Materials as Anti-Counterfeit Markers for Electronic Components - The project will solicit academic laboratory participation for doing testing that demonstrates the 'robustness' of the use of Botanical DNA material as anti-counterfeit markers for electronic components. Request analysis of candidate DNA marker materials utilizing current DNA manipulation technology. This would be done especially in light of results from (1) above.

Understanding the dynamic activity of neural circuits is central to the NIH BRAIN Initiative. This FOA seeks applications for proof-of-concept testing and development of new technologies and novel approaches for largescale recording and manipulation of neural activity to enable transformative understanding of dynamic signaling in the nervous system. In particular, we seek exceptionally creative approaches to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and/or temporal scales, in any region and throughout the entire depth of the brain. It is expected that the proposed research may be high-risk, but if successful could profoundly change the course of neuroscience research. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Where appropriate, applications are expected to integrate appropriate domains of expertise, including biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

The Algorithms for Threat Detection (ATD) program supports research on new ways to use spatiotemporal datasets to develop quantitative models of human dynamics. The objectives include improved representation of complicated group dynamics and the development of algorithms that can process data in near real-time to accurately identify unusual events and forecast future threats indicated by those events.

The Algorithms for Threat Detection (ATD) program will support research projects to develop the next generation of mathematical and statistical algorithms for analysis of large spatiotemporal datasets with application to quantitative models of human dynamics. The program is a partnership between the Division of Mathematical Sciences (DMS) at the National Science Foundation (NSF) and theNational Geospatial Intelligence Agency (NGA).

The Algorithms for Threat Detection (ATD) program will support research projects to develop the next generation of mathematical and statistical algorithms for analysis of large spatiotemporal datasets with application to quantitative models of human dynamics. The program is a partnership between the Division of Mathematical Sciences (DMS) at the National Science Foundation (NSF) and the National Geospatial Intelligence Agency (NGA).

On behalf of the Governor's Office of Health Transformation (OHT), and the Ohio Departments of Medicaid (ODM), Health (ODH) and Higher Education (ODHE), the Ohio Colleges of Medicine Government Resource Center (GRC) is requesting applications from qualified investigators through the Infant Mortality (IM) Research Partnership to identify interventions and resources needed to improve health outcomes for underserved populations and address the complicated health issue of infant mortality from a systems perspective. The IM Research Partnership seeks to fund multiple research projects in areas including but not limited to: systems dynamics modeling of the impact of the following efforts on infant mortality: improved access to care, safe sleep, and impact of progesterone; predictive modeling for infant mortality; spatial GIS modeling for identifying high-risk communities; and evaluation of the impact of OIMRI home visiting programs.

The Analysis Program supports basic research in that area of mathematics whose roots can be traced to the calculus of Newton and Leibniz.  Given its centuries-old ties to physics, analysis has influenced developments from Newton's mechanics to quantum mechanics and from Fourier's study of heat conduction to Maxwell's equations of electromagnetism to Witten's theory of supersymmetry.  More generally, research supported by Analysis provides the theoretical underpinning for the majority of applications of the mathematical sciences to other scientific disciplines.  Current areas of significant activity include: nonlinear partial differential equations; dynamical systems and ergodic theory; real, complex and harmonic analysis; operator theory and algebras of operators on Hilbert space; mathematical physics; and representation theory of Lie groups/algebras.  Emerging areas include random matrix theory and its ties to classical analysis, number theory, quantum mechanics, and coding theory; and development of noncommutative geometry with its applications to modeling physical phenomena.  It should be stressed, however, that the underlying role of the Analysis Program is to provide support for research in mathematics at the most fundamental level.  Although this is often done with the expectation that the research will generate a payoff in applications at some point down the road, the principal mission of the Program is to tend and replenish an important reservoir of mathematical knowledge, maintaining it as a dependable resource to be drawn upon by engineers, life and physical scientists, and other mathematical scientists, as need arises.

This Funding Opportunity Announcement (FOA) encourages applications for developing and testing innovative theories and computational, mathematical, or engineering approaches to deepen our understanding of complex social behavior. This research will examine phenomena at multiple scales to address the emergence of collective behaviors that arise from individual elements or parts of a system working together. Emergence can also describe the functioning of a system within the context of its environment. Often properties we associate with a system itself are in actuality properties of the relationships and interactions between a system and its environment. This FOA will support research that explores the often complex and dynamic relationships among the parts of a system and between the system and its environment in order to understand the system as a whole.

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 Analysis Program supports basic research in that area of mathematics whose roots can be traced to the calculus of Newton and Leibniz. Given its centuries-old ties to physics, analysis has influenced developments from Newton's mechanics to quantum mechanics and from Fourier's study of heat conduction to Maxwell's equations of electromagnetism to Witten's theory of supersymmetry. More generally, research supported by Analysis provides the theoretical underpinning for the majority of applications of the mathematical sciences to other scientific disciplines. Current areas of significant activity include: nonlinear partial differential equations; dynamical systems and ergodic theory; real, complex and harmonic analysis; operator theory and algebras of operators on Hilbert space; mathematical physics; and representation theory of Lie groups/algebras. Emerging areas include random matrix theory and its ties to classical analysis, number theory, quantum mechanics, and coding theory; and development of noncommutative geometry with its applications to modeling physical phenomena. It should be stressed, however, that the underlying role of the Analysis Program is to provide support for research in mathematics at the most fundamental level. Although this is often done with the expectation that the research will generate a payoff in applications at some point down the road, the principal mission of the Program is to tend and replenish an important reservoir of mathematical knowledge, maintaining it as a dependable resource to be drawn upon by engineers, life and physical scientists, and other mathematical scientists, as need arises.ConferencesPrincipal Investigators should carefully read the program solicitation "Conferences and Workshops in the Mathematical Sciences" (link below) to obtain important information regarding the substance of "conference proposals" (i.e., proposals for conferences, workshops, summer/winter schools, and similar activities). For Analysis c

The Algorithms for Threat Detection (ATD) program will support research projects to develop the next generation of mathematical and statistical algorithms for analysis of large spatiotemporal datasets with application to quantitative models of human dynamics. The program is a partnership between the Division of Mathematical Sciences (DMS) at the National Science Foundation (NSF) and the National Geospatial Intelligence Agency (NGA).

The purpose of this Funding Opportunity Announcement (FOA) is to support the development and validation of modeling and simulation methods and related tools to examine HIV transmission dynamics, make epidemic projections, and estimate the impact of HIV treatment and prevention. Investigators are expected to share these resources with other researchers. Funding for the final fourth year is dependent upon achieving applicant-proposed and pre-award negotiated Go/No-Go criteria.

The James S. McDonnell Foundation is currently accepting applications for its Postdoctoral Fellowship Award in Understanding Dynamic and Multi-Scale Systems. The program supports scholarship and research directed toward the discovery and refinement of theoretical and mathematical tools that can contribute to the continued development of the study of complex, adaptive, nonlinear systems. The program's emphasis is on the development and application of theory and tools used in the study of complex research questions and not on particular fields of research per se. To that end, fellowship awards are designed to provide students with opportunities to pursue postdoctoral training and research opportunities aligned with their interest in obtaining additional skills and experience and that might not otherwise be available.     

The Defense Sciences Office at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals that will enable and demonstrate new design capabilities for complex adaptive systems. Proposed research should develop and/or exploit innovative approaches in mathematical abstraction and composition for the design of dynamic, adaptive and resilient systems with unified understanding of system structures, behaviors and interactions across multiple spatiotemporal scales.