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This Funding Opportunity Announcement (FOA) solicits applications to develop highly innovative computational approaches for interpreting sequence variants in the non-protein-coding regions of the human genome. The goal is to develop methods that analyze whole-genome sequence data by integrating data sets, such as ones on genome function, phenotypes, patterns of variation, and other features, to identify or substantially narrow the set of variants that are candidates for affecting organismal function leading to disease risk or other traits. The accuracy of the computational approaches developed should be assessed using experimental data.

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.

This funding opportunity announcement (FOA) encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that propose development of a broad base of innovative technologies in biomedical computing, informatics, and Big Data Science that will support rapid progress in areas of scientific opportunity in biomedical research. It is expected that this research and development is conducted in the context of important biomedical and behavioral research problems. As such, applications are intended to develop enabling technologies that could apply to the interests of most NIH Institutes and Centers and range from basic biomedicine to research in all relevant organ systems and diseases. Major themes of research include collaborative environments; data integration; analysis and modeling methodologies; and novel computer science and statistical approaches. New opportunities are also emerging as large and complex data sets are becoming increasingly available to the research community.

The purpose of this Funding Opportunity Announcement (FOA) and the companion FOA is to solicit applications for computational and functional analysis of gene networks and complex pathways that confer susceptibility to severe mental illnesses. These studies should leverage existing diverse multi-scale datasets and apply a combination of cutting-edge bioinformatics, computational predictive modeling, and systems biology approaches to identify and begin to evaluate novel genetic factors and molecular networks underlying functional pathways relevant to psychiatric disorders to verify their relationship or causality with disease/disease risk.  The computational model predictions should be further replicated through independent datasets and confirmed using biological measures from existing and/or new experimental data.

The National Science Foundation (NSF), through the Directorate for Engineering, the Directorate of Computer and Information Science and Engineering Division of Computer and Network Systems, and the Directorate for Mathematical and Physical Sciences Division of Materials Research, along with the U.S. Food and Drug Administration (FDA), through its Center for Devices and Radiological Health (CDRH), have established the NSF/FDA Scholar-in-Residence Program at FDA. This program comprises an interagency partnership for the investigation of scientific and engineering issues concerning emerging trends in medical device technology. This partnership is designed to enable investigators in science, engineering, and computer science to develop research collaborations within the intramural research environment at the FDA. This solicitation features three flexible mechanisms for support of research at the FDA: 1) Principal Investigators at FDA; 2) Postdoctoral Researchers at FDA; and 3) Graduate Students at FDA.

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

Candidates must hold a Ph.D. (or equivalent) in chemistry, computational or evolutionary molecular biology, computer science, economics, mathematics, neuroscience, ocean sciences (including marine biology), physics, or a related field; Candidates must hold a tenure track (or equivalent) position at a college, university or other degree-granting institution in the United States or Canada;  Candidates must normally be no more than six years from completion of their most recent Ph.D. (or equivalent) as of the year of their nomination.  (That is, most recent Ph.D. must have been awarded on or after September 2007.)** While Fellows are expected to be at an early stage of their research careers, there should be strong evidence of independent research accomplishments. Candidates in all fields are normally below the rank of associate professor and do not hold tenure, but these are not strict requirements. The Alfred P. Sloan Foundation welcomes nominations of all candidates who meet the traditional high standards of this program, and strongly encourages the participation of women and members of underrepresented minority groups.

The purpose of this Funding Opportunity Announcement (FOA) is to support the development of advanced computational, bioinformatic and statistical tools to determine the functional relevance of genetic variants associated with mental disorders of complex etiologies identified through genome-wide association or sequencing studies. The overarching goal of this initiative is to support the development of innovative computational methods that facilitate the elucidation of the functionality of genetic variants associated with mental illness, taking into account the added complexities and nuances of brain diseases, and to ultimately inform the identification and validation of potential targets for novel treatment development. This FOA should be used when two or more sites are needed to complete the study. For a linked set of collaborative R01s, each site must have its own Program Director/Principal Investigator and the set of linked applications provide a mechanism for cross-site coordination, quality control, database management, statistical analysis, and reporting.

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.

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.

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

The purpose of this Funding Opportunity Announcement (FOA) is to support the development of advanced computational, bioinformatic and statistical tools to determine the functional relevance of genetic variants associated with mental disorders of complex etiologies identified through genome-wide association or sequencing studies. The overarching goal of this initiative is to support the development of innovative computational methods that facilitate the elucidation of the functionality of genetic variants associated with mental illness, taking into account the added complexities and nuances of brain diseases, and to ultimately inform novel treatment development based on human biology.

FDA's CDER is seeking a computational modeling approach to study the effects of mucociliary clearance on localized drug absorption in the nasal cavity. The modeling approach would utilize computational fluid dynamics (CFD) simulations of inhalation and droplet/particle transport to provide regional nasal spray deposition data, while the three-dimensional mucociliary clearance model would demonstrate localized drug absorption and indicate the efficacy of drug products that target specific nasal regions. The model should be adaptable to cases of interindividual variability, which may include variations in mucociliary clearance rates, changes in nasal geometry, and the presence of relevant disease states (e.g., nasal inflammation, changes in mucus properties, etc.).

The purpose of this initiative is to support Genomic Centers for Infectious Diseases (GCID) to promote broad use and expand the application of genomics technologies and computational analysis to understand infectious diseases, with an emphasis on pathogens, their interaction with the host and microbiome, and to aid in the development of novel genomics-based tools to diagnose, prevent and treat infectious diseases. The GCID will support innovative technology development in all aspects of genomics, including the use of synthetic and genome editing technologies as well as functional genomics to address basic, translational, and clinically relevant questions in host-pathogen interactions. The knowledge generated, including research data, analytical software tools, computational models, experimental protocols, and reagents, is expected to be widely disseminated to the scientific community through publicly accessible databases and reagent repositories.

In celebrating its 350th anniversary, Merck KGaA, Darmstadt, Germany offers a series of research grants to stimulate innovative research in challenging areas of future importance. Merck KGaA, Darmstadt, Germany intends to provide several research grants of up to EUR 350,000 per year for 3 years in various research areas with the option of extension or expansion. Grants are offered for research in the following areas: Healthy Lives / Drug Discovery: Challenge 1: What is the next game-changing molecule or technology to help cure cancer or autoimmune disease? Life Reimagined / Synthetic Biology: Challenge 1: What is the next generation production technology for biologics? Challenge 2: Can you revolutionize microbiome research? Materials & Solutions: Challenge 1: Can you develop a new generation of intelligent materials? Challenge 2: Can you develop advances in characterization, control and surface chemistry? Challenge 3: Can you develop better atomic layer processes - from modelling to materials? Digitalization / Computing: Challenge 1: How can in-silico research benefit from deep learning or quantum computing?

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) 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 purpose of this funding opportunity announcement (FOA) is twofold: 1. to accelerate translational and clinical Phase I and II a/b safety and efficacy studies for substantiating measurable functional benefits of probiotic/prebiotic components and/or their combinations; and; 2. to understand the underlying mechanisms of their action(s), and variability in responses to these interventions. This FOA calls for interdisciplinary collaborations across scientific disciplines engaged in microbiome and pro/prebiotic research including, but not limited to: nutritional science, microbiology, virology, microecology and microbiome, genomics, immunology, computational biology, chemistry, bioengineering, as well as integration of omics and computational approaches in DNA technologies.

This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting dynamical features and patterns in complex brain data. It is expected that the tools developed under this FOA will be made widely available to the neuroscience research community for their use and modification. Investigative studies should be limited to validity testing of the tools being developed.

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.