1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
Schmidt Sciences invites proposals for its 2026 Science of Trustworthy AI program, supporting technical research that improves our ability to understand, predict, and control risks from frontier AI systems.
The program funds work across three research aims: characterizing misalignment in frontier AI systems, developing generalizable measurements and interventions for AI safety, and overseeing AI systems with superhuman capabilities including multi-agent risks. Research areas include interpretability, robustness, alignment, and risk prediction.
Tier 1 awards up to $1M support focused investigations, while Tier 2 awards of $1M-$5M+ fund larger multi-year collaborative efforts across multiple institutions. Schmidt Sciences also provides compute resources, software engineering support, and API credits with frontier model providers. Preference is given to multi-PI collaborations.
This is a rigorous scientific research program focused on technical AI safety, not policy analysis.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →Key questions and narrative sections extracted from the solicitation.
Aim 1: Characterize and forecast misalignment in frontier AI systems
Aim 2: Develop generalizable measurements and interventions
Aim 3: Oversee AI systems with superhuman capabilities and address multi-agent risks
Scoring criteria used to review proposals for this grant.
According to the current listing, eligibility includes: Open globally to individual researchers, research teams, research institutions, and multi-institution collaborations across universities, national laboratories, institutes, and nonprofit research organizations. Preference given to proposals from collaborations among multiple PIs and labs. Cross-border partnerships encouraged. Indirect costs cannot exceed 10%. Funded projects must comply with applicable law without lobbying or political activity. Confirm the full requirements in the official notice before applying.
The current listing shows tier 1: Up to $1 million for focused investigations (1-3 years). Tier 2: $1 million to $5 million or more for larger multi-year collaborative efforts (1-3 years). Indirect costs capped at 10%. Additional support includes compute resources, software engineering support, and API credits with frontier model providers. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was May 17, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Schmidt Sciences 2026 Science of Trustworthy AI RFP is funded by Schmidt Sciences. Verify program details on the funder's official page before applying.
This listing is flagged as international in scope. Check the official notice for country-specific restrictions before applying.
Applications go through the funder's official portal — the Apply Now link on this page goes there directly.
Schmidt Sciences invites proposals for the 2026 Science of Trustworthy AI RFP, funding technical research that advances the science of building trustworthy AI systems. The program addresses three interconnected research aims: understanding why frontier AI systems develop misaligned goals that fail under distribution shift or pressure (Aim 1), creating valid evaluations and interventions to control what AI systems learn (Aim 2), and developing oversight mechanisms for superhuman AI capabilities and managing multi-agent risks (Aim 3). Beyond direct funding, awardees receive computing resources including GPUs and CPUs, software engineering support, API credits with frontier model providers, and access to a research community. The program is open globally and encourages cross-institutional and cross-geographic collaborations. Indirect costs are capped at 10% of total direct costs.
The VESRI Climate Modeling Challenge is a Schmidt Sciences call, run through the Virtual Earth System Research Institute, that funds research teams to make coupled climate models faster to improve, more reproducible and more accurate. The challenge will fund up to five teams with up to 2 million US dollars each over 24 months to implement and test new methods, explicitly including machine learning, improved representation of physical processes, and advanced calibration workflows. Expressions of intent were invited through 11 September 2026, with a full proposal stage to follow for shortlisted teams. The framing matters: VESRI is targeting the engineering bottleneck in climate modelling rather than climate science questions as such. Coupled model development cycles are slow because calibration is expensive and model updates are hard to reproduce, and the challenge asks teams to demonstrate methods that shorten that loop. Proposals that treat machine learning as an end in itself, rather than as a means to faster and more reproducible model iteration, are mismatched to the brief. VESRI already coordinates hundreds of climate and data scientists across nine projects, 17 countries and 65 research institutions, and Schmidt Sciences has granted 26 million dollars to researchers working on translating climate models into climate action, so this challenge extends an established portfolio. Applicants should expect to compete against teams with existing coupled-model infrastructure, and a proposal without access to a working coupled model to improve is at a structural disadvantage.
Schmidt Sciences opened a 'Scaling AI Safety for a Multi-Agent World' program with awards up to $1 million and an August 8, 2026 deadline. Against a backdrop of federal research slowdowns, here is why private science philanthropy matters more than ever, how these funders differ from federal agencies, and how researchers should approach them.
Read articleSchmidt Sciences' 2026 Science of Trustworthy AI RFP closes May 17 with two funding tiers — up to $1M (Tier 1) and $1–5M+ (Tier 2) over 1–3 years, with a 10% indirect cost cap. The three research aims target misalignment under distribution shift, predictive-validity evaluations, and oversight of superhuman systems. Here is why the structure favors team-based proposals.
Read articleThe U.S. Government Policy for Stopping High-Risk Life Sciences Research, released July 28, 2026 under EO 14292 and implemented at NIH through NOT-OD-26-101, replaces mitigation with prohibition. It bans dangerous gain-of-function research outright, gates potential DGOF behind government-wide review, and creates International Research of Concern — a research-security regime wearing biosafety clothing. Penalties run to five-year debarment and False Claims Act exposure.
Read article