Research and Training Funding

Funding Opportunity Announcements

Browse below for Data Science Funding Opportunity Announcements.

This page last reviewed on August 7, 2019

Feed last updated: July 04 2020 9:53 pm
Title FOA Number Organization Release Date Expiration Date Purpose Search Terms
Development of the INCLUDE (Investigation of Co-occurring Conditions across the Lifespan to Understand Down syndromE) Project Data Coordinating Center RFA-OD-20-007 NIH Dec 13 2019 Feb 15 2020 The objective of this FOA is to support the development of the Data Coordinating Center for the NIH INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE (INCLUDE) project, which consists of the following components: a Data Portal Core, a Data Management Core, and an Administrative and Outreach Core. The goal of the web-based Data Portal is to accelerate discovery of etiology and biologic pathways underlying the comorbidities of Down syndrome by facilitating access to and querying of data from cohorts of individuals with Down syndrome. The Data Portal will facilitate access to aggregated and harmonized data to empower analyses among the Down syndrome research community, as well as the broader scientific community. The Data Management Core will work with INCLUDE investigators and other data generators to facilitate data collection, processing, and harmonization. The Administrative and Outreach Core will oversee administrative activities, work closely with a Steering Committee and INCLUDE program staff, and provide outreach and education to the research community on using the Data Portal.
Development of Innovative Informatics Methods and Algorithms for Cancer Research and Management (R21 Clinical Trial Optional) RFA-CA-20-007 NCI Jan 23 2020 Nov 19 2020 The purpose of this Funding Opportunity Announcement (FOA) is to invite exploratory/developmental research grant applications (R21) for the development of innovative methods and algorithms in biomedical computing, informatics, and data science addressing priority needs across the cancer research continuum including cancer biology, cancer treatment and diagnosis, early cancer detection, risk assessment and prevention, cancer control and epidemiology, and/or cancer health disparities. As a component of the NCI's Informatics Technology for Cancer Research (ITCR) Program, this FOA encourages applications focused on the development of novel computational, mathematical, and statistical algorithms and methods that can considerably improve acquisition, management, analysis, and dissemination of relevant data and/or knowledge. The central mission of ITCR is to promote research-driven informatics technology across the development lifecycle to address priority needs in cancer research. In order to be successful, there must be a clear rationale for how the proposed informatics method or algorithm is novel and how it will benefit the cancer research field. Potential applicants who are interested in downstream technology development, from prototyping to hardening and adaptation, should consult the other companion FOAs listed above.
Data Science Research: Personal Health Libraries for Consumers and Patients (R01 Clinical Trial Optional) PAR-19-072 NLM Nov 19 2018 Jul 31 2021 The National Library of Medicine seeks applications for novel informatics and data science approaches that can help individuals gather, manage and use data and information about their personal health. A goal of this program is to advance research and application by patients and the research community through broadly sharing the results via publication, and through open source mechanisms for data or resource sharing. data science, informatics
Data Harmonization, Curation and Secondary Analysis of Existing Clinical Datasets (R61/R33 Clinical Trial Not Allowed) RFA-NS-20-007 NINDS Oct 30 2019 Mar 18 2020 This FOA invites applications from multidisciplinary teams to perform secondary data analysis, using existing datasets from two or more multi-site clinical research projects, to address scientific and clinical hypotheses relevant to neurological disorders and conditions within the NINDS mission. In this phased funding mechanism, applications are required to systematically and comprehensively perform cross-project data harmonization and curation, assessed using Go/No-go data-quality metrics, prior to funding of the second phase of data analyses. Consistent with the FAIR (findable, accessible, interoperable and reusable) data principles, this funding opportunity expects open-source cataloging of the processes and tools used for harmonization, curation, and analysis, as well as controlled access to the curated datasets.
Clinical High Risk for Psychosis: Data Processing, Analysis, and Coordination Center (U24 Clinical Trial Not Allowed) RFA-MH-20-341 NIMH Nov 27 2019 Feb 01 2020 This Funding Opportunity Announcement (FOA) invites applications for a Data Processing, Analysis, Management and Coordinating Coordination Center (DACDPACC) to support aggregation and analysis of existing data related to Clinical High Risk for psychosis (CHR) and oversight and coordination of CHR research networks to be funded under a future NIMH FOA described in NOT-MH-19-042.
Clinical High Risk for Psychosis Research Network (U01 Clinical Trial Not Allowed) RFA-MH-20-340 NIMH Nov 27 2019 Feb 01 2020 The purpose of this Funding Opportunity Announcement (FOA) is to solicit applications to establish research network(s) focused on rapidly recruiting a sufficient number of participants to dissect the heterogeneity of the clinical high risk for psychosis (CHR) syndrome so as to predict differential CHR outcomes. Results from these studies will inform future treatment development efforts.
Clinical and Translational Science Award (U54 Clinical Trial Optional) PAR-18-940 NCATS Sep 27 2018 Aug 16 2021 The purpose of this funding opportunity announcement (FOA) is to invite applications to participate in the Clinical and Translational Science Award (CTSA) Program which supports high quality translational science and clinical research locally, regionally and nationally and fosters innovation in research methods, training, and career development.
BRAIN Initiative: Team-Research BRAIN Circuit Programs - TeamBCP (U19 Clinical Trial Required) RFA-NS-19-002 NINDS Aug 29 2018 Oct 31 2020 This FOA will support integrated, interdisciplinary research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies. The goal will be to support programs with a team science approach that can realize meaningful outcomes within 5-plus years. Awards will be made for 5 years, with a possibility of one competing renewal. Applications should address overarching principles of circuit function in the context of specific neural systems underlying sensation, perception, emotion, motivation, cognition, decision-making, motor control, communication, or homeostasis. Applications should incorporate theory-/model-driven experimental design and should offer predictive models as deliverables. Applications should seek to understand circuits of the central nervous system by systematically controlling stimuli and/or behavior while actively recording and/or manipulating relevant dynamic patterns of neural activity and by measuring the resulting behaviors and/or perceptions. Applications are expected to employ approaches guided by specified theoretical constructs, and are encouraged to employ quantitative, mechanistic models where appropriate. Applications will be required to manage their data and analysis methods in a prototype framework that will be developed and used in the proposed U19 project and exchanged with other U19 awardees for further refinement and development. Model systems, including the possibility of multiple species ranging from invertebrates to humans, can be employed and should be appropriately justified. Budgets should be commensurate with multi-component teams of research expertise including neurobiologists, statisticians, physicists, mathematicians, engineers, computer scientists, and data scientists, as appropriate - that seek to cross boundaries of interdisciplinary collaboration.
BRAIN Initiative: Team-Research BRAIN Circuit Programs - TeamBCP (U19 Clinical Trial Not Allowed) RFA-NS-19-003 NINDS Aug 29 2018 Oct 31 2020 This FOA will support integrated, interdisciplinary research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies. The goal will be to support programs with a team science approach that can realize meaningful outcomes within 5-plus years. Awards will be made for 5 years, with a possibility of one competing renewal. Applications should will incorporate overarching principles of circuit function in the context of specific neural systems underlying sensation, perception, emotion, motivation, cognition, decision-making, motor control, communication, or homeostasis. Applications should incorporate theory-/model-driven experimental design and should offer predictive models as deliverables. Applications should seek to understand circuits of the central nervous system by systematically controlling stimuli and/or behavior while actively recording and/or manipulating relevant dynamic patterns of neural activity and by measuring the resulting behaviors and/or perceptions. Applications are expected to employ approaches guided by specified theoretical constructs, and are encouraged to employ quantitative, mechanistic models where appropriate. Applications will be required to manage their data and analysis methods in a prototype framework that will be developed and used in the proposed U19 project and exchanged with other BRAIN U19 awardees for further refinement and development. Model systems, including the possibility of multiple species ranging from invertebrates to humans, can be employed and should be appropriately justified. Programs should employ multi-component teams of research expertise including neurobiologists, statisticians, physicists, mathematicians, engineers, computer scientists, and data scientists, as appropriate - that seek to cross boundaries of interdisciplinar
BRAIN Initiative: Secondary Analysis and Archiving of BRAIN Initiative Data (R01 Clinical Trial Not Allowed) RFA-MH-20-120 NIMH Apr 10 2019 Jun 12 2020 The BRAIN Initiative and the neuroscience field as a whole is generating massive and diverse research data across different modalities, spatiotemporal scales and species in efforts to advance our understanding of the brain. The data types are being produced through development and application of innovative technologies in high-throughput -omics profiling, optical microscopy, electron microscopy, electrophysiological recording, macroscale neuroimaging, neuromodulation, and others. The BRAIN Initiative has made significant investments in the development of an infrastructure to make data available to the research community in a useful way. This infrastructure includes data archives, data standards, and software for data integration, analysis and machine learning. This Funding Opportunity Announcement (FOA) encourages secondary analysis of the large amounts of existing data related to the BRAIN Initiative. The data do not need to be held in one of the funded BRAIN Initiative data archives, but the data must be held in a data archive that is readily accessible to the research community. Support will be provided for innovative analysis of relevant existing datasets using conventional or novel analytic methods, data science techniques, and machine learning approaches. Support may also be requested to prepare and submit existing data into any of the BRAIN Initiative data archives. Investigators should not underestimate the time and effort that may be necessary to curate or harmonize data. Analyzed data, models and analytical tools generated under this FOA are expected to be deposited into an appropriate data archive. Since the BRAIN Initiative data archives are mostly making the data available to the research community through cloud-based storage, depositing the analyzed data, models and tools are expected to enhance opportunities to create a data sandbox where investigators can easily compare the results of their analysis with those from other research groups. data science, data integration, machine learning, data standards

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