Notice NOT-CA-19-045 from the NIH Guide for Grants and Contracts

Notice NOT-CA-19-044 from the NIH Guide for Grants and Contracts

Notice NOT-NS-19-051 from the NIH Guide for Grants and Contracts

Notice NOT-OD-19-098 from the NIH Guide for Grants and Contracts

Funding Opportunity RFA-HL-20-005 from the NIH Guide for Grants and Contracts. This Funding Opportunity Announcement (FOA) seeks grant applications to optimally and sustainably address late-stage implementation research questions to address scaling up evidence-based interventions at the population level for prevention and management of hypertension in low- and middle-income countries and small island developing states. For the purposes of this FOA, late-stage implementation research is defined as research to identify strategies to achieve sustainable uptake of proven-effective interventions in routine clinical and public health and community-based settings and maximize the positive impact on population health. Each awarded project is to conduct late-stage implementation research in one of six geographical regions (e.g., East Asia and the Pacific; Europe and Central Asia; Latin America and the Caribbean; Middle East and North Africa; South Asia; Sub-Saharan Africa). As a group, awardees will constitute a research alliance for hypertension implementation science research in low-resource settings with capabilities for addressing scale-up of evidence-based interventions at the population level for the prevention and management of hypertension. This program is not intended to support research that can be conducted primarily in and/or by the United States or other high-income institutions that do not meet eligibility criteria. This FOA uses the bi-phasic, milestone driven UG3/UH3 cooperative agreement mechanism. Awards made under this FOA will initially support a two-year milestone-driven needs assessment and planning, with possible transition to an implementation (UH3) phase of up to 4 additional years. Only UG3 projects that meet the scientific milestones and award requirements of the UG3 phase may transition to the UH3 phase. Applications submitted in response to this FOA must address both the UG3 and UH3 phases and are expected to include plans for project management and performance milestones for each phase.

£40000 - £50000 per annum: Hyper Recruitment Solutions (HRS): HRS INFORMATION ONLY - KEY HINTS AND TIPS: We are currently looking for a Bioinformatics Algorithm Developer to join a leading company based in the Cambridge... Cambridge

Funding Opportunity RFA-AI-19-030 from the NIH Guide for Grants and Contracts. The objective of this Funding Opportunity Announcement (FOA) is to support the evaluation of early stage diagnostics and novel diagnostic strategies for Tuberculosis (TB) in the context of existing clinical diagnostic algorithms in TB endemic countries. Evaluation studies should focus on: 1) proof-of principle studies of novel diagnostic tests and strategies and 2) provide feedback to diagnostic developers on the performance of the technology and most effective strategy for use of a diagnostic technology in an endemic setting.

Notice NOT-HL-19-693 from the NIH Guide for Grants and Contracts

Notice NOT-HL-19-692 from the NIH Guide for Grants and Contracts

Notice NOT-HL-19-694 from the NIH Guide for Grants and Contracts

Notice NOT-HL-19-691 from the NIH Guide for Grants and Contracts

Notice NOT-NS-19-053 from the NIH Guide for Grants and Contracts

Funding Opportunity PAR-19-246 from the NIH Guide for Grants and Contracts. The NIH Research Education Program (R25) supports research education activities in the mission areas of the NIH. The over-arching goal of this National Institute on Drug Abuse (NIDA) R25 program is to support educational activities that encourage individuals from diverse backgrounds, including those from groups underrepresented in the biomedical and behavioral sciences, to pursue further studies or careers in substance abuse and addiction research.

Notice NOT-NS-19-052 from the NIH Guide for Grants and Contracts

Notice NOT-NS-19-056 from the NIH Guide for Grants and Contracts

Notice NOT-NS-19-055 from the NIH Guide for Grants and Contracts

Notice NOT-NS-19-054 from the NIH Guide for Grants and Contracts

Notice NOT-DK-19-013 from the NIH Guide for Grants and Contracts

Notice NOT-AR-19-032 from the NIH Guide for Grants and Contracts

Funding Opportunity RFA-MH-20-120 from the NIH Guide for Grants and Contracts. 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.