Grants for Public housing authorities - Federal

This funding opportunity supports research centers focused on understanding how biological sex differences affect women's health, promoting interdisciplinary collaboration and workforce diversity in the scientific community.

This funding opportunity supports the establishment of a center that fosters collaboration between researchers in substance use epidemiology and prevention to develop effective strategies for preventing substance use and related issues.

Synopsis: NOFO # DD24-0051 solicits non-research, cooperative agreement applications to conduct population-based surveillance of congenital heart defects (CHD) to describe health outcomes including health equity, with the goal of identifying opportunities to improve the health of all people living with CHD. This project will involve a required component (A) and an optional component (B). The population included in this surveillance activity can be an entire state or a region within a state. Individuals with CHD should be identified through existing data sources including the jurisdiction birth defects surveillance system, electronic health records, administrative data (e.g., Medicaid/Medicare, hospital discharge), or other sources available to funding recipients. Background: Congenital heart defects (CHD) affect about 1% of all births in the United States, and are a leading cause of birth defect-associated infant mortality, morbidity, and healthcare costs. Improvements in early detection and treatment of CHD and consequently in survival have resulted in many people, including those affected by a severe CHD, living into adolescence and adulthood. An estimated two million persons in the U.S. are living with a CHD, including over one million adults; about 12% of these affected adults have a severe CHD. Most current efforts to conduct population-based surveillance of CHD have focused on monitoring newborns. However, little data exist on the descriptive epidemiology of CHD beyond early childhood in the U.S. Despite the public health burden, the lack of population-based surveillance precludes reliable data on people with CHD, their survival, healthcare utilization, and characteristics associated with long-term outcomes. Through this surveillance activity, these data will be assessed, enabling and informing efforts to improve the health and well-being of people with CHD. Objectives: Component A objectives include: (1) assess survival, comorbidities, healthcare utilization during the period 2021-2023, and characteristics associated with long-term outcomes among people with CHD; (2) assess health equity among people with CHD; (3) examine state and national healthcare policies that have an impact on people with CHD; (4) examine COVID-19 and related data such as health care utilization during the pandemic among people with CHD; and (5) work with local/state partners to use site-specific CHD data. Component B objectives include: (1) develop and refine a machine learning algorithm for the surveillance data collected through Component A; and (2) apply this machine learning algorithm to data collected from all recipients funded through Component A.

This funding opportunity supports experienced researchers looking to expand their expertise or shift their career focus through advanced training and research experiences at various institutions.

This funding opportunity supports innovative research into the biological mechanisms behind complex brain disorders, targeting a wide range of eligible applicants including universities, nonprofits, and small businesses.

This funding opportunity supports a wide range of organizations in developing innovative drug therapies for Alzheimer's disease and related dementias, focusing on non-traditional treatment targets and requiring collaboration with NIH throughout the clinical trial process.

This funding opportunity supports innovative research into new risk factors for liver cancer, particularly focusing on non-viral causes and their interactions with established risks, aimed at improving prevention strategies in the U.S. population.

This funding opportunity provides financial support for researchers and organizations to investigate the factors driving tuberculosis transmission and develop innovative methods for prevention and detection in high-burden areas.

This funding opportunity supports initiatives that plan to improve health equity and reduce health disparities for women and girls of reproductive age from racial and ethnic minority and underserved communities by integrating comprehensive healthcare services.

This funding opportunity provides financial support for U.S.-based researchers and institutions to develop innovative human models that simulate radiation injuries, aiming to improve understanding and treatment of radiation exposure effects.

The Silvio O. Conte Digestive Diseases Research Core Centers grant, provided by the NIDDK, supports collaborative research on digestive and liver diseases by offering shared resources to enhance productivity and foster new ideas, centered around a theme within the NIDDK's mission.

This funding opportunity provides financial support to rural Alaska communities for critical infrastructure projects that require non-federal matching funds, focusing on areas such as energy, broadband, housing, and waterfront infrastructure.

This funding opportunity supports collaborative research projects in neurology, encouraging diverse teams to tackle significant scientific questions that advance the field through interdependent studies.

This funding opportunity supports the development of diverse cancer research cohorts to improve understanding of cancer causes and outcomes, particularly among underrepresented populations.

This funding opportunity supports collaborative research projects that use simulation modeling to improve cancer control strategies and outcomes for specific cancer types, aiming to enhance public health decision-making and survivor quality of life.

This funding opportunity provides support for high-risk clinical trials focused on infectious, immunologic, and allergic diseases, encouraging innovative research that can lead to new treatments and therapies.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic computer science and applied mathematics research in the fundamentals of Artificial Intelligence (AI) for science. Specifically, advancements in this area are sought that can enable the development of: Foundation models for computational science; Automated scientific workflows and laboratories; Scientific programming and scientific-knowledge-management systems; Federated and privacy-preserving training for foundation and other AI models for science; and Energy-efficient AI algorithms and hardware for science. The development of new AI techniques applicable to multiple scientific domains can accelerate progress, increase transparency, and open new areas of exploration across the scientific enterprise. SUPPLEMENTARY INFORMATION AI is one of the most powerful technologies of our time[1] and DOE is at the forefront of research and development in AI technologies for enabling scientific discovery and innovation. Core components of the scientific method remain unchanged: Observation, Hypothesis, Experiments, and Analysis. However, DOE recognizes that abundant sources of data, high-performance computing (HPC) and networking, energy-efficient algorithms, and AI-related technologies can be harnessed to significantly accelerate and expand the impact of scientific research. The breadth of applications spans climate science, cybersecurity and electric grid resilience, biotechnology, microelectronics, disaster response, and beyond. Research to address national priorities will require advances and AI innovations in high-level capabilities such as: monitoring and predicting the onset of real-world anomalies and extreme events; adaptive strategies to control the real-time behavior of complex systems, infrastructure, and processes; approaches for the optimal development and design of physical systems; decision-support for planning, risk, and policy formulation; and tools that synthesize scientific knowledge and accelerate the design, manufacturing, testing, and optimization of new technologies. The focus of ASCR research and development investments is on the underlying approaches for AI-enhanced scientific and engineering capabilities and to significantly transform the scientific method for accelerated discovery and innovation. Realizing the next generation of AI for science will require innovations in both hardware and algorithms. Future AI-enabled scientific workflows are expected to use Machine Learning (ML) to enhance numerical modeling and data analysis along with technologies that process natural and computer-programming languages. DOEs exascale supercomputers[2] are some of the Nations most powerful systems for large-scale AI training and for tasks integrating AI, modeling, simulation, and data analysis. These exascale and future systems complement the vast array of other AI-enabled HPC and edge systems, including automated laboratories and facilities, that will significantly accelerate scientific progress in the coming decades. DOEs scientific community has collectively articulated important research directions toward realizing the promise of AI for science and other DOE missions in the recently-released AI For Science, Energy, and Security report [1], building on the preceding AI for Science report [2], and complementing the report on Opportunities and Challenges from Artificial Intelligence and Machine Learning for the Advancement of Science, Technology, and the Office of Science Missions [3]. The research directions highlighted in these reports, and others, appear prominently in the National Artificial Intelligence Research and Development Strategic Plan [4]. This FOA addresses a broad spectrum of research priorities described in these documents that are critical to enabling trustworthy AI for scientific applications advancing human understanding and addressing national needs. [1] For additional background on the promise and importance of AI R, see the OMB/OSTP Memorandum on Multi-Agency Research and Development Priorities for the FY 2025 Budget (August 2023) https://www.whitehouse.gov/wp-content/uploads/2023/08/FY2025-OMB-OSTP-RD-Budget-Priorities-Memo.pdf, and the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (October 2023) https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/ [2] For more information on ASCRs exascale supercomputers, and other HPC resources, available as national user facilities, see https://science.osti.gov/ascr/Facilities/User-Facilities

The purpose of the Mentored Quantitative Research Career Development Award (K25) is to attract to NIH-relevant research those investigators whose quantitative science and engineering research has thus far not been focused primarily on questions of health and disease. The K25 award will provide support and "protected time" for a period of supervised study and research for productive professionals with quantitative (e.g., mathematics, statistics, economics, computer science, imaging science, informatics, physics, chemistry) and engineering backgrounds to integrate their expertise with NIH-relevant research. This Funding Opportunity Announcement (FOA) is designed specifically for applicants proposing research that does not involve leading an independent clinical trial, a clinical trial feasibility study, or an ancillary clinical trial. Applicants to this FOA are permitted to propose research experience in a clinical trial led by a mentor or co-mentor. Applicants proposing a clinical trial or an ancillary clinical trial as lead investigator, should apply to the companion FOA ().

This funding opportunity supports U.S.-based cancer research institutions to enhance their research infrastructure and collaborative efforts in cancer prevention, treatment, and care.

This funding opportunity provides financial support to non-profits, local governments, and tribal entities to develop and implement programs that prevent and end homelessness, particularly for youth and vulnerable populations, while promoting access to essential resources and services.