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This Funding Opportunity Announcement (FOA) solicits applications developing computational models of immunity that advance understanding of the mechanisms required to induce and/or maintain protective immunity to infectious pathogens, other than HIV, and/or vaccines against such pathogens. The main goal of this FOA is to advance development and application of computational models of immunity that are refined through iterative immunological experimentation to validate and improve the utility and robustness of the computational models. Another goal of this FOA is to make the computational models and data developed under this initiative readily available to the broader research community for further refinement or direct use in biological experimentation. This program will also support workshops and symposia to foster the use of computational models of immunity by the broader research community.

The functionality of the NeuroImaging Tools and Resources Collaboratory (NITRC) has enabled three distinct components to flourish: Resources Registry (NITRC-R): a collaboratory enabling the distribution, enhancement, and adoption of neuroimaging tools and resources. Image Repository (NITRC-IR): a curated repository of free neuroimaging datasets meeting global standards. Computational Environment (NITRC-CE): a freely downloadable or pay-as-you-go virtual computing cloud-based platform that is pre-configured with popular neuroimaging tools. NITRC-R has become the major web-based collaborative environment enabling the distribution, enhancement, and adoption of neuroinformatics resources. It currently hosts more than 1,000 tools and resources in areas such as magnetic resonance imaging (MRI), computed tomography (CT), optical imaging, positron emission tomography/single-photon emission computed tomography (PET/SPECT), electroencephalography/magnetoencephalography/electrocorticography (EEG/MEG/ECoG), computational neuroscience, and imaging genomics. Since NITRC's inception, there have been more than 10 million total downloads of tools from NITRC-R.

Computational neuroscience provides a theoretical foundation and a rich set of technical approaches for understanding complex neurobiological systems, building on the theory, methods, and findings of computer science, neuroscience, and numerous other disciplines. Through the CRCNS program, the National Science Foundation (NSF), the National Institutes of Health (NIH), the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF), the French National Research Agency (Agence Nationale de la Recherche, ANR), the United States-Israel Binational Science Foundation (BSF), and Japan's National Institute of Information and Communications Technology (NICT) support collaborative activities that will advance the understanding of nervous system structure and function, mechanisms underlying nervous system disorders, and computational strategies used by the nervous system.

The proliferation of mobile and Internet-of-Things (IoT) devices, and their pervasiveness across nearly every sphere of our society, continues to raise questions about the architectures that organize tomorrow’s compute infrastructure. At the heart of this trend is the data that will be generated as myriad devices and application services operate simultaneously to digitize a complex domain like a smart building or smart industrial facility. A key shift is from edge devices consuming data produced in the cloud to edge devices being a voluminous producer of data. This shift reopens a broad variety of system-level research questions concerning data placement, movement, processing and sharing. Importantly, the shift also opens the door to compelling new applications with significant industrial and societal impact in domains such as healthcare, manufacturing, transportation, public safety, energy, buildings, and telecommunications. Edge computing is broadly defined as a networked systems architectural approach in which compute and storage resources are placed at the network edge, in proximity to the mobile and IoT devices.

The Microsoft Foundation is inviting applications for its Dissertation Grants program. The program supports PhD students at North American universities who are underrepresented in the field of computing and pursuing research aligned to the research areas carried out by Microsoft Research. Through the program, recipients will receive funding of up to $25,000 for the 2020-21 academic year as well as an invitation to the PhD Summit, a two-day workshop in the fall held at one of Microsoft Research's labs where fellows will meet with Microsoft researchers and other top students to share their research. Fellows must be aligned in research areas as defined by Microsoft Research, which include artificial intelligence; audio and acoustics; computer vision; graphics and multimedia; human-computer interaction; human language technologies; search and information retrieval; data platforms and analytics; hardware and devices; programming languages and software engineering; security, privacy, and cryptography; systems and networking; algorithms; mathematics; ecology and environment; economics; medical, health, and genomics; social sciences; and technology for emerging markets.

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.

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.

The primary objective of this FOA is to stimulate innovative Convergent Neuroscience (CN) approaches to establish causal and/or probabilistic linkages across contiguous levels of analysis (e.g., gene, molecule, cell, circuit, system, behavior) in an explanatory model of psychopathology. In particular, applicants should focus on how specific constituent biological processes at one level of analysis contribute to quantifiable properties at other levels, either directly or as emergent phenomena.  Although not required, it is preferable that applications link at least three levels of analysis and include an emphasis on genetics. The projects under this FOA will develop novel methods, theories, and approaches through a CN team framework, bringing together highly synergistic inter/transdisciplinary teams from neuroscience and "orthogonal" fields (e.g., data/computational science, physics, engineering, mathematics, and environmental sciences). Successful teams will combine, expand upon, or develop conceptual frameworks and theoretical approaches, and build explanatory computational models that connect contiguous levels of analysis. Such frameworks, theories, and computational explanatory models should be validated through experimental approaches to elucidate biological underpinnings of complex behavioral (including cognitive and affective) outcomes in psychopathology. Additionally, a goal of this program is to advance research in CN by creating a shared community framework of resources which may be used by the broader research community to further research, as such, successful team will have robust plan for sharing data and other resources.

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.

CISE's Division of Computer and Network Systems (CNS) supports research and education projects that develop new knowledge in two core programs: Computer Systems Research (CSR) program; and Networking Technology and Systems (NeTS) program. Proposers are invited to submit proposals in three project classes, which are defined as follows: Small Projects - up to $500,000 total budget with durations up to three years; Medium Projects - $500,001 to $1,200,000 total budget with durations up to four years; and Large Projects - $1,200,001 to $3,000,000 total budget with durations up to five years.

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 Funding Opportunity Announcement (FOA) solicits proposals for research projects that will use computational approaches to test the validity of dimensional constructs in the NIMH Research Domain Criteria matrix (or similar constructs based on comparable criteria). Some elements of the RDoC matrix have been updated since its first release, but a thorough data-driven validation that broadly explores, compares, and validates the constructs within the matrix has not been performed. This FOA seeks research that addresses the following questions: do the different domains of behavior segregate from each other? How much do they rely on distinct vs. overlapping neural circuits? What are the relationships between domains, constructs and subordinate subconstructs, both in terms of their correlational structure and their underlying neural circuitry? By answering these questions, proposals will test integrative models of functioning and identify dysregulation in psychopathology-related mechanisms that may cut across traditional diagnostic categories and may change over time. This FOA seeks to promote projects where the computational and the experimental components are well-integrated. The ultimate goal is to advance translational research that will identify novel classification approaches and/or treatment targets, and lead to more effective and timely interventions for serious mental illness.

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 goal of the interagency Smart and Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information science and engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population. Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

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 invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

This FOA invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

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 request for a literature review and subsequent computer modeling falls within the framework of the Project FAIL-SAFE research effort. The National Association of State Fire Marshals Fire Research and Education Foundation (NASFM Foundation) has undertaken Project FAIL-SAFE in an effort to provide quantifiable data on the integration and inter-relation of fire protection systems in modern construction techniques. The literature review is designed to determine what is currently known in this area and identify areas where additional knowledge gains are needed. The computer modeling will follow the literature review to test and provide initial answers to the identified knowledge gaps from the literature review.

The goal of the interagency Smartand Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information scienceand engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population.Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

The goal of the interagency Smart and Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information science and engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population. Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.