The National Library of Medicine (NLM) seeks applications for research projects that drive groundbreaking innovation and advanced development in the fields of bioinformatics, translational bioinformatics, and computational biology. The primary goal of this initiative is to support the creation and implementation of cutting-edge methods, tools, and approaches that can transform the landscape of biomedical data science. This NOFO aims to address the growing need to leverage transformative technologies — such as artificial intelligence (AI), machine learning, and large-scale computational platforms — to extract actionable knowledge from vast, diverse, and complex biological datasets. By enabling more effective interpretation and integration of multi-dimensional biological and biomedical da...

The Centers of Research Excellence in Science and Technology (CREST) program provides support to enhance the research capabilities of minority-serving institutions (MSIs) as defined in this solicitation’s Eligibility section, through effective integration of education and research. The CREST program, composed of the CREST Centers, the CREST Postdoctoral Research Program, and the projects supported by this CREST-RISE solicitation, promotes the development of new knowledge, enhancements of the research productivity of individual faculty and postdoctoral scholars, and an expanded presence of research doctoral students in science, technology, engineering, and mathematics (STEM) disciplines, especially those from underrepresented groups. CREST-RISE is the component of the CREST program...

The U.S. Geological Survey Southwest Biological Science Center (SBSC) seeks to provide financial assistance for a research project to help build a program to use new remote sensing platforms to improve understanding of how southwestern U.S. ecosystems work and for management options that can best provide ecosystem services in these challenging ecosystems. This program will focus on remote sensing tools that are best for dryland ecosystems, on biological soil crust communities, and on using remote sensing to inform land management options. The work will also focus on using artificial intelligence (AI), machine learning, and other cutting edge data analysis tools to analyze a range and scale of data that was previously not possible.Nearly 40% of the United States are arid and semiarid eco...

The Pathways to Enable Secure Open-Source Ecosystems (PESOSE) program supports the translation of open-source science and engineering-focused research products into safe and sustainable ecosystems that address national and societal challenges. Open-source tools such as software, hardware, machine learning models, languages, and data platforms are designed to be shared as they are publicly-accessible and modifiable. These tools spark innovation in critical fields as varied as artificial intelligence (AI) and cloud computing, banking, healthcare, research, education, next-gen manufacturing, mobility, and National security (including cybersecurity). PESOSE supports the creation of managing organizations for these ecosystems, ensuring strong governance, distributed development, and broad us...

 1.     Digital Ecosystems:•  High speed, intelligent, data-driven decision making for complex operations•  Data discovery, information and knowledge management•  Rapid adaptable policy and enforcement for digital environments 2.     Hydrodynamics:•  Computational hydrodynamic tools•  Seakeeping and loads in extreme seas•  Maneuvering and control•  Maneuvering in waves•  Cavitation•  Hull-propulsor interaction•  Hydrodynamic modeling of operations: in an ice slurry; multi-body interactions; propulsor hull system optimization; appendage characterization and scaling; near-surface and near-shore maneuvering and control modeling deve...

The Collaboratory to Advance Mathematics Education and Learning (CAMEL) for K-12 initiative aims to advance mathematics learning and education through purposeful collaboration that draws on the interdisciplinary Science of Learning (including neuroscience; cognitive, developmental, and social sciences; computer science; machine learning; engineering; and education research), deep experiences in education practice and teaching, and innovations in the use of data science, AI and technology. Through an agreement with philanthropic partners, including the Walton Family Foundation (WFF), CAMEL consists of two phases. Phase I invites proposals for the creation of new research networks to support the generation of high value datasets that aim to advance math learning and education. These resea...

Society relies on chemical processes to turn raw materials into useful products. The Chemical Process Systems (CPS) program invests in fundamental research on chemical and biochemical processes to make them more efficient, sustainable, and resilient. New CPS technologies for manufacturing, biotechnology, critical minerals, energy, food, and other national priorities will help make the U.S. more competitive and secure. Research supported by the CPS program covers the full breadth of chemical and biochemical process innovation. It spans reaction engineering and molecular thermodynamics; reactor design; catalysis; electrochemical systems; separations; and process design. The program encourages proposals that connect the molecular scale to process and plant scales. The CPS program explores ...

Wildland fire is a powerful force on the planet, one that is rapidly accelerating in complexity beyond our current understanding. A new approach is needed. This approach requires a proactive and scalable perspective that recognizes the variety and connectedness of components of wildland fire. Coordinated scientific research and education that enables large-scale, cross-cutting breakthroughs to transform our understanding of wildland fire is urgently needed. In an era of rapid change, our society needs forward-looking research built on new frameworks that will realign our relationship with wildland fire. The Fire Science Innovations through Research and Education (FIRE) program invites innovative multidisciplinary and multisector investigations focused on convergent research and educatio...

Summary: The fiscal year 2026 (FY26) Prostate Cancer Research Program (PCRP) Data Science Award (DSA) supports research that develops or uses quantitative and analytical approaches, processes and/or systems to obtain knowledge and insight from large and/or complex sets of prostate cancer data in one or more of the following research areas: Analysis of clinically annotated datasets; analysis of -omics data; artificial intelligence and machine learning; bioinformatics; computational biology; digital pathology; epidemiology; and medical imaging. All applications must address one of the FY26 PCRP Overarching Challenges. Distinctive Features: This funding mechanism allows for multiple Principal Investigators (PIs). Only the initiating PI will submit a pre-application, but all PIs will need t...

The purpose of the Rehabilitation Engineering Research Centers (RERC) program is to improve the effectiveness of services authorized under the Rehabilitation Act by conducting advanced engineering research on and development of innovative technologies that are designed to solve particular rehabilitation problems or to remove environmental barriers. The purpose of this RERC is to conduct research on, develop, and evaluate Artificial Intelligence (AI)-driven assistive and rehabilitation technologies that enhance independence, participation, and quality of life for people with disabilities. Many existing assistive and rehabilitation technologies lack adaptability, personalization, and seamless integration into daily life. AI and machine learning (ML) offer trans-formative potential to addr...

The Emerging Mathematics in Biology (eMB) program seeks to stimulate the development of innovative mathematical theories, techniques, and approaches to investigate challenging questions of great interest to biologists and public health policymakers. It supports truly integrative research projects in mathematical biology that address challenging and significant biological questions through novel applications of traditional, but nontrivial, mathematical tools and methods or the development of new mathematical theories particularly from foundational mathematics, including the mathematical foundation of Artificial Intelligence/Deep Learning/Machine Learning (AI/DL/ML) enabling explainable AI or mechanistic insight. The program emphasizes the uses of mathematical methodologies to advanc...

The purpose of this funding opportunity is to support research addressing barriers that limit progress toward more effective open- and closed-loop diabetes control systems. This may include research that addresses: 1) innovation of sensing relevant analytes/physiologic signals; 2) novel formulation and delivery of hormones; 3) artificial intelligence (AI)/machine learning (ML)-driven tools/algorithms; and 4) digital twin modeling to augment decision support and automated control systems with the goal of improving glycemic control, reducing burden of care, and enhancing quality of life of people with T1D].This NOFO is associated with the Special Diabetes Program (https://www.niddk.nih.gov/about-niddk/research-areas/diabetes/type-1-diabetes-special-statutory-funding-program/about-special-...

TCRGP focuses on development of research capacity at Tribal colleges, specifically in agriculture, natural resources, and human sciences. The program aims to teach leadership skills, knowledge, and qualities that are necessary to prepare students to be competitive with other students for agricultural and related careers in the private sector, government, and academia. Of interest are the projects involving innovative agricultural technologies, including artificial intelligence (AI), data science, robotics, and other cutting edge digital tools. NIFA encourages incorporation of opportunities for training undergraduate students in these areas to equip them with the foundational knowledge and skills necessary to adapt to and thrive in an increasingly digital society and expose them to educa...

This program will advance scientific community datasets to enable scientific discovery and innovation using artificial intelligence (AI) and other methods. Its goal is to increase the value that can be derived from existing scientific datasets by leveraging novel methods and artificial intelligence (AI). This will unlock new AI-driven insights. It can enable interdisciplinary research. It also enables investigations outside of the original motivation for data collection and analysis. The program seeks to 1) apply AI-based capabilities to feature extraction and metadata generation, and the integration of multiple datasets. 2) Develop robust data pipelines necessary for automated analysis of existing datasets and similar use-cases by AI tools and systems. 3) Augment and/or harmonize exist...