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In 2013, a new NSF-funded petascale computing system, Blue Waters, was deployed at the University of Illinois. The goal of this project and system is to open up new possibilities in science and engineering by providing computational capability that makes it possible for investigators to tackle much larger and more complex research challenges across a wide spectrum of domains. The purpose of this solicitation is to invite research groups to submit requests for allocations of resources on the Blue Waters system. Proposers must show a compelling science or engineering challenge that will require petascale computing resources. Proposers must also be prepared to demonstrate that they have a science or engineering research problem that requires and can effectively exploit the petascale computing capabilities offered by Blue Waters. Proposals from or including junior researchers are encouraged, as one of the goals of this solicitation is to build a community capable of using petascale computing.

In 2013, a new NSF-funded petascale computing system, Blue Waters, was deployed at the University of Illinois.  The goal of this project and system is to open up new possibilities in science and engineering by providing computational capability that makes it possible for investigators to tackle much larger and more complex research challenges across a wide spectrum of domains.  The purpose of this solicitation is to invite research groups to submit requests for allocations of resources on the Blue Waters system. Proposers must show a compelling science or engineering challenge that will require petascale computing resources. Proposers must also be prepared to demonstrate that they have a science or engineering research problem that requires and can effectively exploit the petascale computing  capabilities offered by Blue Waters.  Proposals from or including junior researchers are encouraged, as one of the goals of this solicitation is to build a community capable of using petascale computing.

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), and the United States-Israel Binational Science Foundation (BSF) 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. 

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), and the United States-Israel Binational Science Foundation (BSF) 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. Two classes of proposals will be considered in response to this solicitation:Research Proposals describing collaborative research projects, andData Sharing Proposals to enable sharing of data and other resources.

The Society for Neuroscience, the world's largest organization of scientists and physicians dedicated to understanding the brain and the nervous system, works to advance scientific exchange, support the neuroscience community, educate and engage the public, and advocate for the field. In support of this mission, SfN is accepting applications for the Swartz Prize for Theoretical and Computational Neuroscience. Supported by the Swartz Foundation, the prize honors an individual whose activities have produced a significant cumulative contribution to theoretical models or computational methods in neuroscience or who has made a particularly noteworthy recent advance in theoretical models or computational neuroscience.

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 Swartz Prize, supported by the Swartz Foundation, honors an individual whose activities have produced a significant cumulative contribution to theoretical models or computational methods in neuroscience or who has made a particularly noteworthy in theoretical or computational neuroscience.

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.

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.

This Funding Opportunity Announcement (FOA) solicits applications 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 versus overlapping neural circuits? What are the relationships between domains, constructs and subordinate sub-constructs, both in terms of their correlational structure and their underlying neural circuitry? By answering these questions, proposed research projects þffwill 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 illnesses.

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.

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.

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.

TRANSLATIONAL MEDICINE AND THERAPEUTICS: The goal of the PhRMA Foundation's Translational Medicine and Therapeutics Program is to promote the development and use of experimental and computational methods in an integrative approach towards clinical needs in diagnosis, treatment and prevention. This can involve enhanced understanding of human biological and disease processes but requires a strong translational component. This program will support the concepts of Translational Medicine and Therapeutics as defined by the Foundation: "Translational medicine and therapeutics is a discipline focused on bridging experimental and computational technologies and discoveries in the research laboratory to their application in clinical practice. Examples of research components include activities in molecular and cellular biology, pathophysiology, systems biology, bioinformatics, modeling and simulation, and other quantitative sciences to connect basic biological concepts and entities to directly address unmet medical needs. The goals are to use clinical observation as the basis for hypothesis generation to further basic research and to efficiently advance the product of basic research to patients." Translational Medicine and Therapeutics awards will advance training and support career development of scientists engaged in research that significantly integrates cutting-edge technologies with advanced biological, chemical, and pharmacological sciences and engineering methodologies in such areas as (but not restricted to): * Genetics (Molecular, Pharmaco-, Population, Medical) * Genomics (Functional, Structural, Toxico-, Pharmaco-, Comparative) * Systems (Biology and Pharmacology) * Pathways and networks * Integrative biology * Modeling and simulation * Target Identification and Validation * Biomarker Discovery and Validation * Vaccine Development * Molecular Epidimiology * Imaging * Disease Modeling

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.

This Funding Opportunity Announcement (FOA) intends to accelerate the integration and use of scalable technologies and tools to enhance and reinvigorate brain cell census research, including the development of technology platforms and/or resources that will enable a swift and comprehensive survey of brain cell types and circuits. Of particular interest are those that will (a) improve technology and resource platforms to remove limitations and bottlenecks in the current pipeline of brain cell census data generation; (b) integrate experimental and computational methods to enhance capabilities of cell census data generation and analysis and to reduce barriers to hypothesis-driven research; (c) generate a substantial amount of spatiotemporal cell census data and/or resources to demonstrate the utility of the improved technology and resource platforms; and (d) conduct comparative studies by using proper criteria to evaluate and benchmark quality of biospecimen, performance of cell census tools/technologies, and effectiveness of computational approaches. The projects funded under this FOA will align with the overarching goals of the BRAIN Initiative Cell Census Network (BICCN) and are expected to generate a substantial amount of cell census data using the proposed technologies or via collaboration with the BICCN.

This Funding Opportunity Announcement (FOA) solicits applications for research projects that will apply computational approaches to develop parametrically detailed behavioral assays across mental-health relevant domains of function. These projects should focus on behavior in humans and test computational models in healthy subjects. NIMH is particularly interested in the study of behavioral measures, models, and parameters that have the potential for back-translation from humans to animals, especially for pre-clinical therapeutics development, and/or in models that have the potential to be extended to clinical populations.  

This funding opportunity announcement (FOA) invites applications for mentored career enhancement (K18) awards in research areas that are highly relevant to the NIH BRAIN Initiative. This career enhancement program will support development of research capability for the BRAIN Initiative, with specific emphasis on cross-training independent investigators in a substantively different area of neuroscience, neuroethics, or in a quantitative and physical discipline (e.g., physics, chemistry, engineering, computer science, mathematics); and vice versa, cross-training independent investigators trained in a quantitative or physical discipline proposing to gain in-depth training in a high-priority area of neuroscience. The research project conducted under this K18 should enhance the candidate's ability to significantly contribute to or lead projects that investigate questions central to the goals of the BRAIN Initiative. Eligible candidates are independent investigators at any faculty rank or level.

This funding opportunity announcement (FOA) invites applications for mentored career enhancement (K18) awards in research areas that are highly relevant to the NIH BRAIN Initiative. This career enhancement program will support development of research capability for the BRAIN Initiative, with specific emphasis on cross-training independent investigators in a substantively different area of neuroscience, neuroethics, or in a quantitative and physical discipline (e.g., physics, chemistry, engineering, computer science, mathematics); and vice versa, cross-training independent investigators trained in a quantitative or physical discipline proposing to gain in-depth training in a high-priority area of neuroscience. The research project conducted under this K18 should enhance the candidate's ability to significantly contribute to or lead projects that investigate questions central to the goals of the BRAIN Initiative. Eligible candidates are independent investigators at any faculty rank or level.

This Funding Opportunity Announcement (FOA) enables data-driven drug repositioning and combination therapy for Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) by developing computational methods and data resources and/or integrating computational approaches with proof-of-concept efficacy studies in cell-based models, animal models, and/or humans.

This solicitation extends the Collaborative Research in Computational Neuroscience program for three years. Proposals for collaborations involving Japan are now supported through a new partnership with the National Institute of Information and Communications Technology. Please see the proposal preparation instructions and country-specific instructions and limitations in Sections V and VIII of this solicitation, and the companion documents published by CRCNS partner agencies referenced in Section VIII. The description of scientific topics and approaches has been updated in Section II of this solicitation. Agency contacts have been updated in Section VIII. Results from prior NSF, NIH, and/or CRCNS support must be included in the Project Description if any PI or co-PI identified on the project has received NSF funding, NIH funding, or CRCNS funding from another participating agency, with a start date in the past five years.