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The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research. Initially the program will limit the field to these four areas that stand to directly benefit from a grounding in formal methods: computer networks, cyber-human systems, machine learning, and operating/distributed systems. However other field(s) may emerge as priority areas for the program in future years, subject to the availability of funds.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research. This solicitation limits the field to the following areas that stand to directly benefit from a grounding in formal methods: computer networks, cyber-human systems, distributed /operating systems, embedded systems, and machine learning. Other field(s) may emerge as priority areas for the program in future years, subject to the availability of funds.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research. This solicitation limits the field to the following areas that stand to directly benefit from a grounding in formal methods: computer networks, cyber-human systems, distributed /operating systems, embedded systems, and machine learning. Other field(s) may emerge as priority areas for the program in future years, subject to the availability of funds.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers. The first group consists of researchers in the area of formal methods, which, for the purposes of this solicitation, is broadly defined as principled approaches based on mathematics and logic, including modeling, specification, design, program analysis, verification, synthesis, and programming language-based approaches. The second group consists of researchers in the "field," which, for the purposes of this solicitation, is defined as a subset of areas within computer and information science and engineering that currently do not benefit from having established communities already developing and applying formal methods in their research.

On the occasion of its 350th anniversary, Merck KGaA, Darmstadt, Germany will fund innovative projects in applied biophysical & analytical research. Projects will be based on the following challenges: · Challenge 1: Analytical technologies for antibodies and antibody-drug conjugates, as well as technologies to determine drug target engagement, or the level of protein or nucleic acid or metabolic biomarkers. · Challenge 2: Analytical technologies for display materials or semiconductors (Liquid Crystals, OLED Materials, Quantum Materials, Reactive Mesogens, Photoresist Materials). E.g. Spectroscopic Methods, MS Hyphenation, Capillary Chromatography and Comprehensive Separation Technologies; Surface analytics for displays (non- or destructive), Sample preparation techniques for ultra-sensitive investigations · Challenge 3: Analytical technologies for the characterization of polymers, chemical imaging, bioanalytical methods or new methods in molecular biology. Technologies of interest for example are: field flow floractionation (FFF), dynamic light scattering (DLS), chemical imaging, new chromatographic techniques, spectroscopic and spectrometric methods, electron paramagnetic resonance (EPR), microwave analytics

Supports mathematical research in areas of science where computation plays a central and essential role, emphasizing design, analysis, and implementation of numerical methods and algorithms, and symbolic methods.  The prominence of computation with analysis of the computational approach in the research is a hallmark of the program.  Proposals ranging from single-investigator projects that develop and analyze innovative computational methods to interdisciplinary team projects that not only create and analyze new mathematical and computational techniques but also use/implement them to model, study, and solve important application problems are encouraged.

The Dynamics, Control and Systems Diagnostics (DCSD) program supports fundamental research on the analysis, measurement, monitoring and control of dynamic systems. The program promotes innovation in the following areas: -Modeling: creation of new mathematical frameworks to apply tools of dynamics to physical systems -Analysis: discovery and exploration of structure in dynamic behavior -Diagnostics: dynamic methods that infer system properties from observations -Control: methods that produce desired dynamic behavior

The Dynamics, Control and Systems Diagnostics (DCSD) program supports fundamental research on the analysis, measurement, monitoring and control of dynamic systems. The program promotes innovation in the following areas: -Modeling: creation of new mathematical frameworks to apply tools of dynamics to physical systems -Analysis: discovery and exploration of structure in dynamic behavior -Diagnostics: dynamic methods that infer system properties from observations -Control: methods that produce desired dynamic behavior

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers

The purpose of this Funding Opportunity Announcement (FOA) is to stimulate translation of scientific discoveries and engineering developments in imaging or spectroscopic technologies into methods or tools that address problems in cancer biology, risk of cancer development, diagnosis, treatment, and/or disease status. A distinguishing feature of each application will be formation of an academic-industrial partnership, which is a strategic alliance of investigators in academic, industrial, and any other entities who work together as partners to identify and translate a technological solution or mitigation of a cancer-related problem. The goals for proposed technologies are imaging applications in clinical trials, clinical research, non-clinical research, and/or patient care. Among other possibilities, they may include pre-clinical imaging investigations or investigations that combine patient specimens and pre-clinical methods, or optimizations of methods across different commercial platforms, sites, or time.

The purpose of this Funding Opportunity Announcement [FOA] submitted through the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to stimulate the development and validation of novel tools and analytical methods to target, identify and characterize non-neuronal cells in the brain. This FOA complements previous and ongoing cell-census and tool development efforts initiated under BRAIN, RFA-MH-14-215 and RFA-MH-14-216, that have focused almost exclusively on neuronal cells. The cutting-edge tools and methods developed under this opportunity should focus specifically on providing improved points of entry into non-neuronal cell-types (glial and vascular) to enable their inventory and characterization within the CNS and help define how these cells interact among each other and with neuronal cells to impact functional circuitries. Plans for validating the utility of the tool/technology/method and demonstrating its advantage over currently available approaches will be an essential feature of a successful application. Tools that can be used in several species or model organisms rather than in a single species are especially desirable.

The Engineering Design and Systems Engineering (EDSE) program supports fundamental research into the basic processes and phenomena of engineering design and systems engineering. The program seeks proposals leading to improved understanding about how processes, organizational structure, social interactions, strategic decision making, and other factors impact success in the planning and execution of engineering design and systems engineering projects. It also supports advances pertaining to engineering design and systems engineering in areas that include, but are not limited to, decision making under uncertainty, including preference and demand modeling; problem decomposition and decision delegation; applications of reverse game theory (mechanism design); computer-aided design; design representation; system performance modeling and prediction; design optimization; uncertainty quantification; domain- or concern-specific design methods; and advanced computational techniques for supporting effective human cognition, decision making, and collaboration. Competitive proposals for novel methods will include a plan to evaluate rigorously the effectiveness and performance of the proposed approach. The EDSE program encourages multidisciplinary collaborations of experts in design and systems engineering with experts in other domains. Of particular interest is research on the design of engineering material systems that leverages the unique aspects of a particular material system to realize advanced design methods that are driven by performance metrics and incorporate processing/manufacturing considerations.

The Chemical Theory, Models and Computational Methods program supports the discovery and development of theoretical and computational methods or models to address a range of chemical challenges, with emphasis on emerging areas of chemical research.  Proposals that focus on established theoretical or computational approaches should involve innovative additions or modifications that substantially broaden their applicability.  Areas of interest include, but are not limited to, electronic structure, quantum reaction dynamics, statistical mechanics, molecular dynamics, and simulation and modeling techniques for molecular systems and systems in condensed phases.  Areas of application span the full range of chemical systems from small molecules to mesoscopic aggregates, including single molecules, biological systems and materials in condensed phases.   Despite the diverse application areas, the goal of the program is to support the development of new theoretical and computational methodologies that have the potential of being broadly applicable to a range of challenging chemical problems. We are particularly interested in fundamental areas of chemical research that are difficult or impossible to address using current synthetic, experimental, and/or computational methodologies.  We encourage the integration of innovative software development with methodological and algorithmic development, especially computational approaches that allow efficient utilization of the high end computers of the future.

The Formal Methods in the Field (FMitF) program aims to bring together researchers in formal methods with researchers in other areas of computer and information science and engineering to jointly develop rigorous and reproducible methodologies for designing and implementing correct-by-construction systems and applications with provable guarantees. FMitF encourages close collaboration between two groups of researchers.

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.

This Biological and Environmental Research/Advanced Scientific Computing Research (BERASCR) Scientific Discovery Thru Advanced Computing (SciDAC) Partnership FOA will enable scientists to conduct complex scientific and engineering computations at a level of fidelity needed to simulate real-world climate conditions, by supporting deep, necessary, and productive collaborations between climate scientists on the one hand and applied mathematicians and computer scientists on the other, that overcome the barriers between these disciplines and consequently fully exploit the capabilities of Department of Energy (DOE) High Performance Computing (HPC) systems in order to accelerate advances in climate science. This SciDAC opportunity targets three particular topics of high-priority for DOE climate research that are expected to be transformed by effective climate-computational partnerships: the development of new and innovative methods to predict sea-level change; the development of a theoretical statistical-numerical framework to improve climate prediction; and the development of improved methods for model component coupling. The next-generation climate model capabilities will contribute to the newly launched Accelerated Climate Model for Energy (ACME) and further its progress toward design of climate codes for leadership class computers and in support of energy science and mission requirements.

The Centers of Excellence in Genomic Science (CEGS) program establishes academic Centers for advanced genome research.  Each CEGS grant supports a multi-investigator, interdisciplinary team to develop innovative genomic approaches to address a particular biomedical problem.  A CEGS project will address a critical issue in genomic science or genomic medicine, proposing a solution that would be a very substantial advance.  Thus, the research conducted at these Centers will entail substantial risk, balanced by outstanding scientific and management plans and very high potential payoff.  A CEGS will focus on the development of novel technological or computational methods for the production or analysis of comprehensive data sets, or on a particular genome-scale biomedical problem, or on other ways to develop and use genomic approaches for understanding biological systems and/or significantly furthering the application of genomic knowledge, data and methods towards clinical applications.  Exploiting its outstanding scientific plan and team, each CEGS will nurture genomic science at its institution by facilitating the interaction of investigators from different disciplines, and by providing training to new and experienced investigators, it will expand the pool of highly-qualified professional genomics scientists and engineers.

The Division of Molecular and Cellular Biosciences (MCB) supports quantitative, predictive, and theory-driven fundamental research and related activities designed to promote understanding of complex living systems at the molecular, subcellular, and cellular levels. MCB is soliciting proposals for hypothesis-driven and discovery research and related activities in four core clusters: Molecular Biophysics Cellular Dynamics and Function Genetic Mechanisms Systems and Synthetic Biology MCB gives high priority to research projects that use theory, methods, and technologies from physical sciences, mathematics, computational sciences, and engineering to address major biological questions.  Research supported by MCB uses a range of experimental approaches--including in vivo, in vitro and in silico strategies--and a broad spectrum of model and non-model organisms, especially microbes and plants. Typical research supported by MCB integrates theory and experimentation.  Projects that address the emerging areas of multi-scale integration, molecular and cellular evolution, quantitative prediction of phenome from genomic information, and development of methods and resources are particularly welcome.

SoftwareInfrastructure for Sustained Innovation (SI2) is a long-term investment focused on realizing a portion of the Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504730) vision and catalyzing new thinking, paradigms and practices in science and engineering. CIF21 envisions a linked cyberinfrastructure architecture that integrates large-scale computing, high-speed networks, massive data archives, instruments and major facilities, observatories, experiments, and embedded sensors and actuators, across the nation and the world, and that enables research at unprecedented scales, complexity, resolution, and accuracy by integrating computation, data, and experiments in novel ways. Software is a primary modality through which CIF21 innovation and discovery will be realized. It permeates all aspects and layers of cyberinfrastructure (from application codes and frameworks, programming systems, libraries and system software, to middleware, operating systems, networking and the low-level drivers). The CIF21 software infrastructure must address the complexity of this cyberinfrastructure, accommodating: disruptive hardware trends; ever-increasing data volumes; data integrity, privacy, and confidentiality; security; complex application structures and behaviors; and emerging concerns such as fault-tolerance and energy efficiency. The programs must focus on building robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery.
 The Division of Advanced Cyberinfrastructure in the Computer & Information Science & Engineering Directorate (CISE/ACI) is partnering with Directorates and Offices across the NSF to support SI2, a long-term comprehensive program focused on realizing a sustained software infrastructure that is an integral part of CIF21.

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 GO Competition is a series of prize challenges to accelerate the development and comprehensive evaluation of grid software solutions. The first GO Competition, Challenge 1, is an algorithm competition focused on the security-constrained optimal power flow (SCOPF) problem for the electric power sector. Awardees under this FOA will be required to participate in Challenge 1. As described in detail in Appendix A1 to this FOA and on the GO Competition website (https://gocompetition.energy.gov/), Challenge 1 is anticipated to launch in the Fall of 2018. Participation in the GO Competition Challenge 1 will be open to anyone that satisfies the applicable requirements in Rules Document specified on the GO Competition website (https://gocompetition.energy.gov/competition-rules), not just those awarded under ARPA-E DE-FOA-0001952. The purpose of this FOA is to provide grants: (i) to further incentivize and identify innovative research for solution methods applicable to Challenge 1, and (ii) to enable broader diversity in team domain expertise, i.e., to encourage teams to participate that do not traditionally focus on the particular problems that are targeted but otherwise have innovative approaches for this class of mathematical programs. While Challenge 1 focuses on a power systems problem, the Challenge and this FOA target a much broader audience (e.g., those specialized in operations research, applied mathematics, optimization methods and algorithms, controls etc.). Existing grid software was designed for a power grid centered on conventional generation and transmission technologies.