1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
Macy Foundation AI in Medical Education Grants is sponsored by The Macy Foundation. Funds projects that integrate AI into medical education to improve healthcare delivery.
Get alerted about grants like this
Save a search for “The Macy Foundation” or related topics and get emailed when new opportunities appear.
Search similar grants →Extracted from the official opportunity page/RFP to help you evaluate fit faster.
The Macy Foundation - Artificial Intelligence in Medical Education Artificial Intelligence in Medical Education Watch the Innovating Med Ed with AI: Insights from the Macy Report Webinar (Hosted by AAMC) Watch the AI in Med Ed Conference Recommendations Webinar (Hosted by AAMC) View AAMC's AI in Academic Medicine Webinar Series 2024 Conference on AI in Medical Education AI in Medical Education: A Grants Program to Advance Innovation in Medical Education As a follow-up to the 2024 Macy conference on AI in Medical Education , the Josiah Macy Jr. Foundation announced a special initiative to fund demonstration projects that advance our understanding of what responsible, effective, and ethical use of AI in medical education will look like in the immediate future.
AI in Medical Education: A Grants Program to Advance Innovation in Medical Education provides support for three demonstration projects, each receiving up to $200,000 over two years. Please see the descriptions of the awarded projects below . materials that emanated from the conference, please visit the Macy Conferences section of the website.
AI in Medical Education: A Grants Program to Advance Innovation in Medical Education Artificial Intelligence Driven Assessment of Resident Surgical Skill Using Video Analysis of Incision Closures in Open Surgery Beth Israel Deaconess Medical Center The grant will leverage computer vision and AI methods to provide automated assessments of surgical skill in open procedures for surgical residents.
Automated video analytics will be captured during incision closures from traditional room video and egocentric recording from smart glasses. The model’s outputs will then be available on a resident-facing web platform designed to support feedback and longitudinal skill tracking. The overall goal is to refine AI-based assessment for open procedures to augment feedback from educators and encourage targeted practice for surgical trainees.
PI: Gabriel Brat, MD, Assistant Professor of Surgery, Beth Israel Deaconess Medical Center, Assistant Professor of Biomedical Informatics, Harvard Medical School Communication Compass: AI-Enhanced Feedback System NYU Grossman School of Medicine Effective patient-physician communication is crucial for high-quality healthcare, but challenging to teach and assess consistently.
Traditional methods often lack the ability to provide timely, objective feedback, leading to gaps in learners' communication skills. To address this, we are developing Communication Compass, an AI-powered system designed to offer personalized, near real-time feedback on learners' communication skills by analyzing ambient audio from patient-physician interactions.
This system will use advanced AI to assess communication across various dimensions and provide structured, rigorously-validated feedback with real examples. We will test this system’s impact on both educational outcomes and patient care through a randomized trial.
Ultimately, Communication Compass aims to create an ethical, scalable framework for improving communication skills in medical education, benefiting learners and patients alike.
PIs: Yuliya Yoncheva, PhD, Research Assistant Professor, Institute for Innovations in Medical Education; Jesse Burk-Rafel, MD, MRes, Director of Research, Institute for Innovations in Medical Education Teaching Future Doctors to Team with AI: A Social Science Approach to Developing and Evaluating Training Methods for Clinical-AI Collaboration Across the ARiSE Network Stanford Center for Biomedical Informatics Research Large language models (LLMs) like ChatGPT are one of the fastest adopted medical technologies in history, now routinely appearing in both clinics and medical classrooms alike.
The stakes are high – multiple studies now show that high-performing artificial intelligence technologies don’t always improve doctor performance. In order to fully recognize the health benefits of these powerful AI systems, medical educators will need to figure out how to better train doctors to work with AI.
The ARiSE Research Network, based at Beth Israel Deaconess Medical Center / Harvard Medical School and Stanford University, will use gold standard social science methodologies to understand how doctors are currently using AI in their clinical care.
They will then run national randomized trials to determine which educational strategies truly boost doctor-AI teamwork in important clinical tasks like diagnosing illnesses, explaining care plans to patients and coordinating treatment. The curricula and assessments from this project will be released openly so medical schools and hospitals around the world can train future doctors to use AI confidently while keeping patients safe.
PIs: Jonathan H. Chen, MD, PhD, Assistant Professor & Director for Medical Education in Artificial Intelligence, Stanford Center for Biomedical Informatics Research; Adam Rodman, MD, MPH, FACP, Hospitalist, Beth Israel Deaconess Medical Center; Assistant Professor, Harvard Medical School Learn more about Our Grantees
Based on current listing details, eligibility includes: Academic institutions and nonprofit organizations. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Varies Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
Yes — AI tools like Granted can help research funders, draft proposal sections, and check compliance. However, always review and customize AI-generated content to reflect your organization's unique strengths and the specific requirements of the solicitation.
Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
The National Leadership Grants for Libraries Program (NLG-L) supports projects that address critical needs of the library and archives fields and have the potential to advance practice and strengthen library and archival services for the American public. Successful proposals will generate results such as new models, tools, research findings, services, practices, and/or alliances that can be widely used, adapted, scaled, or replicated to extend and leverage the benefits of federal investment. Applications to IMLS should both advance knowledge and understanding and ensure that the federal investment made generates benefits to society. Specifically, the goals for this program are to generate projects of far-reaching impact that: • Build the workforce and institutional capacity for managing the national information infrastructure and serving the information and education needs of the public. • Build the capacity of libraries and archives to lead and contribute to efforts that improve community well-being and strengthen civic engagement. • Improve the ability of libraries and archives to provide broad access to and use of information and collections with emphasis on collaboration to avoid duplication and maximize reach. • Strengthen the ability of libraries to provide services to affected communities in the event of an emergency or disaster. • Strengthen the ability of libraries, archives, and museums to work collaboratively for the benefit of the communities they serve. Throughout its work, IMLS places importance on diversity, equity, and inclusion. This may be reflected in an IMLS-funded project in a wide range of ways, including efforts to serve individuals of diverse geographic, cultural, and socioeconomic backgrounds; individuals with disabilities; individuals with limited functional literacy or information skills; individuals having difficulty using a library or museum; and underserved urban and rural communities, including children from families with incomes below the poverty line. Application Process: The application process for the NLG-L program has two phases; applicants must begin by applying for Phase I. For Phase I, all applicants must submit Preliminary Proposals by the September 20th deadline listed for this Notice of Funding Opportunity. For Phase II, only selected applicants will be invited to submit Full Proposals, and only those Invited Full Proposals will be considered for funding. Invited Full Proposals will be due March 20, 2024. Funding Opportunity Number: NLG-LIBRARIES-FY24. Assistance Listing: 45.312. Funding Instrument: G. Category: AR,HU. Award Amount: $50K – $1M per award.
The California Department of Education (CDE) Early Education Division is making approximately .7 million available to expand California State Preschool Program (CSPP) services statewide, appropriated under the 2021 Budget Act. Eligible applicants are local educational agencies (LEAs), including school districts, county offices of education, community college districts, and direct-funded charter schools—both current CSPP contractors and new applicants. Funding supports full-day/full-year or part-day/part-year preschool services for income-eligible children beginning in FY 2024–25. Awards are allocated by county based on Local Planning Council priority areas and application scores, with redistribution provisions if county allocations are underutilized.
F5 STEM Education and AI Grants is sponsored by F5. Global tech company F5's foundation offers grants to nonprofits focused on building the STEM pipeline for women and girls of color, with a newly added emphasis on AI literacy education. High priority is given to programs teaching AI fundamentals or using AI tools in education. In 2025, F5 will fund ten organizations worldwide.