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Bridge2AI Stage 2 advances NIH's flagship biomedical AI initiative from creating ethically sourced, machine-learning-ready datasets to delivering deployable AI tools for specific health challenges.
Stage 2 funds Innovation Funnels that use the Stage 1 AI-ready datasets (voice biomarkers, clinical cardiology, salutogenesis, AI/ML for precision public health) to build diagnostic algorithms, drug discovery platforms, and clinical decision support systems. It also establishes a Network for AI Health Science to develop safety protocols, responsible AI implementation guidance, and ethics frameworks for biomedical AI.
Strong emphasis on FAIR data principles, transparent model documentation, equity, and public trust.
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Or search similar grants →According to the current listing, eligibility includes: U.S. universities, academic medical centers, non-profit research institutions, hospitals, and federal labs. Multidisciplinary consortia required for major mechanisms. International partners allowed under standard NIH terms. Strong fit for teams combining AI methods with deep biomedical domain expertise. Confirm the full requirements in the official notice before applying.
The current listing shows bridge2AI total program commitment is over $130 million through completion. Stage 2 awards span multi-year cooperative agreements (U54, U24, U01 mechanisms) with individual project budgets typically ranging from $1,000,000 to $10,000,000 across project periods. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NIH Common Fund Bridge2AI Stage 2 Innovation Funnels and Network for AI Health Science are due November 30, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NIH Common Fund Bridge2AI Stage 2 Innovation Funnels and Network for AI Health Science is funded by NIH Common Fund (National Institutes of Health). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The NEH Humanities Research Centers on Artificial Intelligence program funds the creation of university-based humanities research centers focused on the ethical, legal, and societal implications of artificial intelligence. Funded centers undertake interdisciplinary humanities-led research that brings ethics, law, history, philosophy, anthropology, religious studies, literature, linguistics, and cultural studies to bear on questions raised by AI systems. Topics include responsible AI governance frameworks, AI and civil rights, AI and labor, cultural impact of generative AI, AI and creative authorship, philosophical foundations of machine reasoning, history of AI thought, and humanistic evaluation of AI safety and alignment. Centers are expected to convene researchers, train new humanities scholars in AI, host public-facing programming, and produce publications and translational tools that inform policy and public understanding. Strong fit for universities seeking to launch sustained interdisciplinary AI humanities research programs in partnership with computer science and other STEM departments.
SaTC 2.0 is NSF's flagship cybersecurity, privacy, and trust research program reorganized to address emerging threats including generative AI security, open-source software security, quantum computing security, and supply chain security. Funded scope covers the bidirectional role of AI as both a cybersecurity threat (adversarial attacks on AI systems, AI-enabled cyberattacks, data poisoning) and a defensive tool (AI for intrusion detection, automated vulnerability discovery, secure-by-design AI). The program supports interdisciplinary collaboration across computer science, mathematics, social and behavioral sciences, and STEM education to build trust in global cyber ecosystems.
NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.
The NIH Common Fund launched PRIMED-AI — Precision Medicine with AI: Integrating Imaging with Multimodal Data — as five coordinated funding opportunities (RFA-RM-27-011 through -015) that build a full pipeline from standards to clinic. Here is how the Playbook, Data-to-Model partnerships, Model-to-Clinic translation, Validation Center, and Logistics Center fit together, what each pays, who is eligible, and how to position before the October 2026 deadlines.
Read articleAvoid common NIH grant proposal mistakes including vague specific aims, weak methodology, and poor budget justification that lead to rejection.
Read articleThe NIH Director's New Innovator Award (DP2, RFA-RM-27-002) closes August 17, 2026, offering roughly 30 Early Stage Investigators up to $475,000 in direct costs a year for five years — $2.375 million total — to pursue bold ideas without the preliminary data a standard R01 demands. Here is how the High-Risk, High-Reward program actually evaluates applications, who qualifies, and why the usual R01 instincts will sink you.
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