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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 goal of theBiomedical Engineering(BME)program is to provide research opportunities to develop novel ideas into discovery-level and transformative projects that integrate engineering and life sciences in solving biomedical problems that serve humanity in the long-term. BME projects must be at the interface of engineering and life sciences, and advance both engineering and life sciences. The projects should focus on high impact transformative methods and technologies. Projects should include methods, models and enabling tools of understanding and controlling living systems; fundamental improvements in deriving information from cells, tissues, organs, and organ systems; new approaches to the design of structures and materials for eventual medical use in the long-term; and novel methods for reducing health care costs through new technologies. The long-term impact of the projects can be related to fundamental understanding of cell and tissue function, effective disease diagnosis and/or treatment, improved health care delivery, or product development.

The goal of theBiomedical Engineering(BME)program is to provide research opportunities to develop novel ideas into discovery-level and transformative projects that integrate engineering and life sciences in solving biomedical problems that serve humanity in the long-term. BME projects must be at the interface of engineering and life sciences, and advance both engineering and life sciences. The projects should focus on high impact transformative methods and technologies. Projects should include methods, models and enabling tools of understanding and controlling living systems; fundamental improvements in deriving information from cells, tissues, organs, and organ systems; new approaches to the design of structures and materials for eventual medical use in the long-term; and novel methods for reducing health care costs through new technologies. The long-term impact of the projects can be related to fundamental understanding of cell and tissue function, effective disease diagnosis and/or treatment, improved health care delivery, or product development.

The mission of the Biomedical Engineering (BME) program is to provide opportunities to develop novel ideas into discovery-level and transformative projects that integrate engineering and life science principles in solving biomedical problems that serve humanity in the long-term.  The Biomedical Engineering (BME) program supports fundamental research in the following BME themes: Neural engineering (brain science, computational neuroscience, brain-computer interface, neurotech, cognitive engineering) Cellular biomechanics (motion, deformation, and forces in biological systems; how mechanical forces alter cell growth, differentiation, movement, signal transduction, transport, cell adhesion, cell cytoskeleton dynamics, cell-cell and cell-ECM interactions; genetically engineered stem cell differentiation with long-term impact in tissue repair and regenerative medicine) The BME projects must be at the interface of engineering and life sciences, and advance both engineering and life sciences.  The projects should focus on high impact transforming methods and technologies. The project should include methods, models and tools of understanding and controlling of living systems; fundamental improvements in deriving information from cells, tissues, organs, and organ systems; new approaches to the design of structures and materials for eventual medical use in the long-term; and new novel methods of reducing health care costs through new technologies. The projects should emphasize the advancement of fundamental engineering knowledge, possibly leading to the development of new methods and technologies in the long-term; and highlight multi-disciplinary nature, integrating engineering and the sciences. The long-term impact of the projects can be related to disease diagnosis and/or treatment, improved health care delivery, or product development.

The Mechanics of Materials program supports fundamental research on the behavior of solid materials and respective devices under external actions.?? A diverse and interdisciplinary spectrum of research is supported with emphasis placed on fundamental understanding that i) advances theory, experimental, and/or computational methods in Mechanics of Materials, and/or ii) uses contemporary Mechanics of Materials methods to address modern challenges in material and device mechanics and physics. Proposed research can focus on existing or emerging material systems across time and length scales. Intellectual merit typically includes advances in fundamental understanding of deformation, fracture, fatigue, and contact through constitutive modeling, multiscale and multiphysics analysis, computational methods, or experimental techniques.??Recent interests comprise, but are not limited to:?? contemporary materials including multiphase materials and material systems, soft materials, active materials, low-dimensional materials, phononic/elastic metamaterials, friction, wear;??multiphysics methods, mechanics at the nano, meso and microscale and multiscale integration thereof, as well as approaches incorporating fundamental understanding of physics and chemistry into the continuum-level understanding of the response characteristics of materials and material systems.

The Engineering and Systems Design (ESD) program supports fundamental research leading to new engineering and systems design methods and practices for specific global contexts.  In particular, ESD seeks intellectual advances in which the theoretical foundations underlying design and systems engineering are operationalized into rigorous and pragmatic methods for a specific context.  In addition, the program funds the rigorous theoretical and empirical characterization of new or existing methods for design and systems engineering, identifying in which global contexts and under which assumptions these methods are effective and efficient.  Such a global context includes both a domain (such as energy systems, consumer products, cyber-physical systems) and an economic, socio-political, environmental and technological context.

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.

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

Imaging systems are commonly used for conducting pavement evaluations. AASHTO Standard Practice for Collecting Images of Pavement Surfaces for Distress Detection (AASHTO Designation: PP 68) addresses the collection of images. However, there are no widely accepted methods for measuring the characteristics of pavement surface images (such as 2-dimensional optical images and 3-dimensional surface elevation images). There are also no widely accepted AASHTO standard practices for the calibration, certification, and verification of such images. Research is needed to identify the characteristics of surface images that are essential for pavement evaluation and develop methods for measuring these characteristics, and also to develop recommended standard practices for implementing these methods. This information will help highway agencies better evaluate image data collection systems and improve the process of pavement condition evaluation. The objectives of this research are to (1) identify and develop methods for measuring the characteristics of surface images used for pavement evaluation and analysis; and (2) develop recommended standard practices for the calibration, certification, and verification of such images, for consideration and adoption by AASHT

The MES program supports research on design, planning, and control of operations in manufacturing enterprises. Research is supported that is both grounded in an interesting and relevant application and requires the development of novel analytical and computational methodologies that may be of broader interest. Topics of interest include supply chain optimization and management; production planning and scheduling; monitoring and control of manufacturing processes; and maintenance and repair. Of particular interest are methods that incorporate increasingly rich enterprise process and product information and models, methods that address sustainability, and methods that incorporate characteristic uncertainty and risk.

The MES program supports research on design, planning, and control of operations in manufacturing enterprises. Research is supported that is both grounded in an interesting and relevant application and requires the development of novel analytical and computational methodologies that may be of broader interest. Topics of interest include supply chain optimization and management; production planning and scheduling; monitoring and control of manufacturing processes; and maintenance and repair. Of particular interest are methods that incorporate increasingly rich enterprise process and product information and models, methods that address sustainability, and methods that incorporate characteristic uncertainty and risk.

The mission of the Biomedical Engineering (BME) program is to provide opportunities to develop novel ideas into discovery-level and transformative projects that integrate engineering and life science principles in solving biomedical problems that serve humanity in the long-term.  The Biomedical Engineering (BME) program supports fundamental research in the following BME themes: Neural engineering (brain science, computational neuroscience, brain-computer interface, neurotech, cognitive engineering) Cellular biomechanics (motion, deformation, and forces in biological systems; how mechanical forces alter cell growth, differentiation, movement, signal transduction, transport, cell adhesion, cell cytoskeleton dynamics, cell-cell and cell-ECM interactions; genetically engineered stem cell differentiation with long-term impact in tissue repair and regenerative medicine) The BME projects must be at the interface of engineering and life sciences, and advance both engineering and life sciences.  The projects should focus on high impact transforming methods and technologies. The project should include methods, models and tools of understanding and controlling of living systems; fundamental improvements in deriving information from cells, tissues, organs, and organ systems; new approaches to the design of structures and materials for eventual medical use in the long-term; and new novel methods of reducing health care costs through new technologies.

The National Institute of Environmental Health Sciences (NIEHS) is announcing the continuation of the Superfund Hazardous Substance Research and Training Program, referred to as Superfund Research Program (SRP) Centers. SRP Center grants will support problem-based, solution-oriented research Centers that consist of multiple, integrated projects representing both the biomedical and environmental science and engineering disciplines; as well as cores tasked with administrative (which includes research translation), data management and analysis, community engagement, research experience and training coordination, and research support functions.  The scope of the SRP Centers is taken directly from the Superfund Amendments and Reauthorization Act of 1986, and includes: (1) advanced techniques for the detection, assessment, and evaluation of the effect on human health of hazardous substances; (2) methods to assess the risks to human health presented by hazardous substances; (3) methods and technologies to detect hazardous substances in the environment; and (4) basic biological, chemical, and physical methods to reduce the amount and toxicity of hazardous substances.

The objective of this Funding Opportunity Announcement is to solicit and competitively seek applications for the development of tools and methods needed to improve the measurement and reduce the uncertainty in the measurement of in-situ maximum principal stress in the deep surface and understand and predict the geomechanical impact of pressure migration due to injection on the storage complex including the underburden and basement formations. The Areas of Interest of this Announcement are Tools and Methods for Determining Maximum Principal Stress in the Deep Surface and Methods for Understanding Impact of Vertical Pressure Migration due to Injection on State of Subsurface Stress.

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 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 EDSE program does not support the development of ad-hoc approaches that lack grounding in theory, nor does it support design activities that do not advance scientific knowledge about engineering design or systems engineering. Prospective investigators are encouraged to discuss research ideas and project scope with the Program Director in advance of proposal preparation and

This Funding Opportunity Announcement (FOA) encourages innovative research to enhance the quality of measurements of dietary intake and physical activity. Applications submitted under this FOA are encouraged to include development of: novel assessment approaches; better methods to evaluate instruments; assessment tools for culturally diverse populations or various age groups, including children and older adults; improved technology or applications of existing technology; statistical methods/modeling to improve assessment and/or to correct for measurement errors or biases; methods to investigate the multidimensionality of diet and physical activity behavior through pattern analysis; or integrated measurement of diet and physical activity along with the environmental context of such behaviors.

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.