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The following program description is offered to provide more in-depth information on scientific and technical areas of interest to the Office of High Energy Physics Long-Term Accelerator R&D Stewardship ("Accelerator Stewardship") program. Please note that this Funding Opportunity Announcement (FOA) is only for opportunities within the Accelerator Research & Development (R&D) Stewardship mission, and that there is a separate Funding Opportunity Announcement for research and development within the objectives of the High Energy Physics (HEP) program. This Accelerator Stewardship FOA is for R&D activities that may impact HEP, but which predominantly impact other non-HEP applications. The mission of the Accelerator Stewardship program is to support fundamental accelerator science and technology development of relevance to many fields beyond HEP, and to disseminate accelerator knowledge and training to the broad community of accelerator users and providers. Further information about the Accelerator Stewardship program may be found at http://science.energy.gov/hep/research/accelerator-stewardship/ .

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The National Science Foundation (NSF) Directorates for Engineering (ENG) and Geosciences (GEO), the Divisions of Integrative Organismal Systems (IOS) and Environmental Biology (DEB), in the Directorate for Biological Sciences (BIO), the Division of Computer and Network Systems in the Directorate Computer and Information Science and Engineering (CISE/CNS), and the Division of Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences, in collaboration with the US Department of Agriculture National Institute of Food and Agriculture (USDA NIFA) encourage convergent research that transforms existing capabilities in understanding dynamic soil processes, including soil formation, through advances in sensor systems and modeling. The Signals in the Soil (SitS) program fosters collaboration among the two partner agencies and the researchers they support by combining resources and funding for the most innovative and high-impact projects that address their respective missions. To make transformative advances in our understanding of soils, multiple disciplines must converge to produce environmentally-benign novel sensing systems with multiple modalities that can adapt to different environments and collect and transmit data for a wide range of biological, chemical, and physical parameters. Effective integration of sensor data will be key for achieving a better understanding of signaling interactions among plants, animals, microbes, the soil matrix, and aqueous and gaseous components. New sensor networks have the potential to inform models in novel ways, to radically change how data is obtained from various natural and managed (both urban and rural) ecosystems, and to better inform the communities that directly rely on soils for sustenance and livelihood.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II). Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering. Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies. Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental 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, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

The Foundational Research in Robotics (Robotics) program supports research on robotic systems that exhibit significant levels of both computational capability and physical complexity. For the purposes of this program, a robot is defined as intelligence embodied in an engineered construct, with the ability to process information, sense, and move within or substantially alter its working environment. Here intelligence includes a broad class of methods that enable a robot to solve problems or make contextually appropriate decisions. Research is welcomed that considers inextricably interwoven questions of intelligence, computation, and embodiment. Projects may also focus on a distinct aspect of intelligence, computation, or embodiment, as long as the proposed research is clearly justified in the context of a class of robots. The focus of the Robotics program is on foundational advances in robotics. Robotics is a deeply interdisciplinary field, and proposals are encouraged that explore the full range of fundamental engineering and computer science research challenges arising in robotics. However, all proposals must convincingly explain how a successful outcome will enable transformative new robot functionality or substantially enhance existing robot functionality. The proposal should clearly articulate how the intellectual contribution of the proposed work addresses fundamental gaps in robotics. Meaningful experimental validation on a physical platform is strongly encouraged. Projects that do not represent a direct fundamental contribution to robotics should not be submitted to the Robotics program.

The Foundational Research in Robotics (Robotics) program supports research on robotic systems that exhibit significant levels of both computational capability and physical complexity. For the purposes of this program, a robot is defined as intelligence embodied in an engineered construct, with the ability to process information, sense, and move within or substantially alter its working environment. Here intelligence includes a broad class of methods that enable a robot to solve problems or make contextually appropriate decisions. Research is welcomed that considers inextricably interwoven questions of intelligence, computation, and embodiment. Projects may also focus on a distinct aspect of intelligence, computation, or embodiment, as long as the proposed research is clearly justified in the context of a class of robots.  The focus of the Robotics program is on foundational advances in robotics. Robotics is a deeply interdisciplinary field, and proposals are encouraged that explore the full range of fundamental engineering and computer science research challenges arising in robotics. However, all proposals must convincingly explain how a successful outcome will enable transformative new robot functionality or substantially enhance existing robot functionality. The proposal should clearly articulate how the intellectual contribution of the proposed work addresses fundamental gaps in robotics. Meaningful experimental validation on a physical platform is strongly encouraged. Projects that do not represent a direct fundamental contribution to robotics should not be submitted to the Robotics program.

This Funding Opportunity Announcement (FOA) seeks clinical research on self-management interventions and technologies that improve health and quality of life in persons needing assistance to optimize and maintain existing functional capabilities, prevent/delay disabilities and navigate their environment. The research focus encompasses maintenance/restorative care that can be tailored to individuals existing functional abilities and interests and is intended to enhance physical, sensory, motor, and mental capabilities. Of particular interest is research designed to maintain functional capabilities in such conditions as cardiac and respiratory insufficiency, movement impairment associated with arthritis, chronic back pain, stroke, and other physical or cognitive disabilities.

This Funding Opportunity Announcement (FOA) seeks clinical research on self-management interventions and technologies that improve health and quality of life in persons needing assistance to optimize and maintain existing functional capabilities, prevent/delay disabilities and navigate their environment. The research focus encompasses maintenance/restorative care that can be tailored to individuals' existing functional abilities and interests and is intended to enhance physical, sensory, motor, and mental capabilities. Of particular interest is research designed to maintain functional capabilities in such conditions as cardiac and respiratory insufficiency, movement impairment associated with arthritis, chronic back pain, stroke, and other physical or cognitive disabilities.

A Simons Collaboration in MPS should address a mathematical or theoretical topic of fundamental scientific importance, where a significant new development creates a novel area for exploration or provides a new direction for progress in an established field. The questions addressed by the collaboration may be concrete or conceptual, but there should be little doubt that answering them would constitute a major scientific milestone. The project should have clearly defined initial activities and goals by which their progress and success can be measured. The support from the foundation should be seen as critical for the objectives of the project.

DOE SC hereby invites applications for support under the Early Career Research Program in the following program areas: Advanced Scientific Computing Research (ASCR); Basic Energy Sciences (BES); Biological and Environmental Research (BER); Fusion Energy Sciences (FES); High Energy Physics (HEP); Nuclear Physics (NP); Isotope R&D and Production (DOE IP); or Accelerator R&D and Production (ARDAP). The purpose of this program is to support the development of individual research programs of outstanding scientists early in their careers and to stimulate research careers in the areas supported by SC.

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.

The CISE-MPS Interdisciplinary Faculty Program in Quantum Information Science is designed to promote research in the area of Quantum Information Science (QIS) by providing resources to allow QIS researchers and researchers from the CISE or MPS disciplines to actively engage in joint research efforts, addressing problems at the interface between the mathematical and physical sciences and computer and information sciences through long-term visits by faculty to a host institution. 

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

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science

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 photonicmaterials, ceramics, and biomaterials. The program supports fundamental research that advances conceptual, analytical, and computational techniques for materials research.

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.

DARPA Defense Sciences Office (DSO) wants to identify and pursue high-risk, high-payoff research initiatives across a broad spectrum of science and engineering disciplines and to transform these initiatives into important, radically new, game-changing technologies for U.S. national security. The current overarching office themes include accelerating scientific discovery, exploring fundamental limits, and expecting the unexpected. In support of this mission, the DSO Office-wide BAA invites proposers to submit innovative basic or applied research concepts in one or more of the following technical areas: Mathematics, Modeling and Design; Physical Systems; Human-Machine Systems; and Social Systems. Each of these areas is described below and includes a list of example research topics that highlight several (but not all) potential areas of interest. Proposals must investigate innovative approaches that enable revolutionary advances. DSO is explicitly not interested in approaches or technologies that primarily result in evolutionary improvements to the existing state of practice.

The purpose of the Mentored Quantitative Research Career Development Award (K25) is to attract to NIH-relevant research those investigators whose quantitative science and engineering research has thus far not been focused primarily on questions of health and disease. The K25 award will provide support and protected time for a period of supervised study and research for productive professionals with quantitative (e.g., mathematics, statistics, economics, computer science, imaging science, informatics, physics, chemistry) and engineering backgrounds to integrate their expertise with NIH-relevant research. Prospective candidates are encouraged to contact the relevant NIH staff for IC-specific programmatic and budgetary information: Table of IC-Specific Information, Requirements and Staff Contacts.

The Simons Foundation's Mathematics and Physical Sciences division invites applications for Collaboration Grants for Mathematicians to stimulate collaboration in the field primarily through the funding of travel and related expenditures. The goal of the program is to support the "mathematical marketplace" by substantially increasing collaborative contacts between mathematicians. The foundation will make a large number of collaboration grants to accomplished, active researchers in the United States who do not otherwise have access to funding that supports travel and visitors.

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.