Updated October 14, 2026
AI in Healthcare Research Grants
Open grants for AI and machine learning research in medicine, clinical care, and biomedical science, from NIH and NSF to disease foundations. Updated daily.
Health and medicine are where AI research funding and biomedical funding meet, and in 2026 that intersection is one of the better-funded places to be. NIH is running dedicated programs to move AI models from the lab into clinical use, the National Library of Medicine continues to fund training in biomedical informatics and data science, and NSF supports work at the boundary of biology and machine learning. Disease-focused funders, from cancer research organizations to professional societies, have added AI-specific calls of their own.
Featured grants
Updated automatically from Atom's grant database. Summaries are AI-generated.Advancing Research at the intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML)
NSF BIO supports research combining biology and AI/ML to advance biological discovery or develop AI/ML methods inspired by biological systems, encouraging interdisciplinary collaboration.
PRIMED-AI: Translating Models to Clinic (UG3/UH3 Clinical Trial Optional)
This NIH grant will fund development and clinical testing of AI tools that combine imaging and other health data to improve personalized care for chronic and other conditions.
PRIMED-AI: Academic-Industrial Partnerships (UG3/UH3 Clinical Trial Optional)
This upcoming NIH grant supports academic-industrial partnerships to develop and test AI tools that integrate medical imaging with other health data to improve personalized care for chronic and other conditions.
The range of fundable work is wide. Programs support clinical decision support, medical imaging, precision medicine, biomarker discovery, and multimodal models that combine records, images, and genomics, alongside the data infrastructure, validation, and fairness research needed to deploy them safely. Clinicians partnering with computational researchers, and machine learning labs looking for a health application, are both well positioned.
This collection gathers open grants for AI and machine learning research in healthcare and biomedical science across federal, foundation, and society funders. It updates as new opportunities post and deadlines pass. Many of these programs favor interdisciplinary teams, so check each listing's eligibility and partnership requirements before you start building an application.
AI-human collaborations in cancer
This grant funds global teams to develop advanced AI agents that work with human researchers to generate and test new cancer research hypotheses, transforming how cancer is studied.
Artificial Intelligence in Communication Sciences and Disorders Research Grant
Supports interdisciplinary research integrating ethical and innovative AI solutions to advance clinical practice, education, and research in communication sciences and disorders.
Postdoctoral Research Fellowships in Biology
This fellowship funds recent PhDs to conduct research and training at the intersection of AI and biology, aiming to advance biotechnology innovation and develop future leaders in the field.
Multimodal AI to Accelerate Precision Medicine for Type 1 Diabetes (U01- Clinical Trials Not Allowed)
This grant funds the development of advanced AI tools to integrate diverse datasets and accelerate precision medicine research for understanding, preventing, and treating Type 1 diabetes.
Artificial Intelligence in Materials Science
Artificial Intelligence in Materials Science supports researchers combining AI and physical theories for materials discovery, simulation, inverse design, and autonomous experiments to advance scientific discovery.
MIT-MGB Seed Program
MIT-MGB Seed Program supports MIT and Mass General Brigham researchers and clinicians in joint research that develops or applies new technologies to transform clinical practice and address health problems.
Fast Grants - Biswas Family Foundation
Fast Grants - Biswas Family Foundation supports researchers pursuing AI- or data-driven health projects, funding models, datasets, tools, and pilot experiments to advance paths toward health breakthroughs.
Kidney Artificial Intelligence Discovery Challenge: From Nebulae to Nephrons
NIH Challenges invites AI-driven research to uncover novel patterns in kidney tissue and multi-omics data, advancing understanding of kidney disease through the Kidney Artificial Intelligence Discovery Challenge.
Computational Approaches to Curation at Scale for Biomedical Research Assets (R01 Clinical Trial Not Allowed)
Grant funds computational methods to enhance curation processes for biomedical data, facilitating rapid access to datasets for transformative research.
Advance Whole-Person Data Integration and Reimagine Data Science Computations and Analytics to Address Chronic Disease Disparity Grand Challenge
NIH Challenges' Grand Challenge seeks innovative, AI-ready data integration and analytics solutions to advance whole-person chronic disease disparities research.
Bloomberg Data Science Ph.D. Fellowship
Bloomberg Data Science Ph.D. Fellowship supports doctoral researchers with funding, mentorship, and research internships to advance AI and data science through publications and open-source contributions.
Fellowship In Informatics
The Fellowship In Informatics by the American College of Radiology immerses radiology residents in hands-on healthcare informatics research, mentorship, and real-world data science projects.
AI for Privacy, Safety, and Security Academic Research Awards
Google's AI for Privacy, Safety, and Security Academic Research Awards fund interdisciplinary research using AI to tackle digital privacy, safety, and security challenges.
AI, Digitization, and Financial Markets
This conference invites research on how AI and digital technologies are reshaping financial markets, with a focus on India and South Asia but open to global perspectives.
Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01 Clinical Trial Optional)
This upcoming NIH grant will fund innovative research developing advanced bioinformatics and computational biology tools to improve biomedical data analysis and health outcomes, encouraging interdisciplinary and technology-driven projects.
The Semantic Precision for AI Retrieval of Knowledge (SPARK) PubMed/PMC Challenge
The SPARK PubMed/PMC Challenge from NIH Challenges seeks AI systems that generate citation-backed, synthesized answers to complex biomedical queries using PubMed and PMC data.
Clinical Trials to Validate AI-Driven Drug Repurposing 2026
Cures Within Reach funds clinical trials using AI to validate repurposed therapies for unsolved diseases, prioritizing rare conditions and explainable AI workflows.
Frequently asked questions
NIH funds much of this work, including programs that move AI models into clinical use and the National Library of Medicine's biomedical informatics and data science programs. NSF supports AI at the intersection with biology, and disease foundations and professional societies run AI-specific calls.
Many do, or strongly prefer one. Programs that aim for clinical use often expect teams that combine machine learning expertise with clinical or biomedical investigators and access to real-world data.
Common areas include medical imaging, clinical decision support, precision medicine, biomarker discovery, multimodal models that combine records and imaging, and research on the validation, fairness, and safe deployment of clinical AI.
Yes, particularly as part of an interdisciplinary team. Several programs and training grants are designed to bring computational researchers into biomedical problems.