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The Alfred P. Sloan Foundation's Exploratory Grantmaking in Technology program supports the development and adoption of AI tools that accelerate scientific research and automate aspects of the scientific process.
Funded areas include foundation models for science (chemistry, biology, materials, physics), AI lab automation and self-driving laboratories, AI-driven literature review and synthesis, machine learning for experimental design, scientific reasoning and hypothesis generation in LLMs, and infrastructure for open scientific AI. Rolling letters of inquiry (no more than two pages) are accepted year-round and emailed to technology@sloan.
org; grants typically range from $100,000 to $400,000.
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Or search similar grants →According to the current listing, eligibility includes: Researchers at universities and nonprofit research institutions; the program prioritizes interdisciplinary, risk-taking work in emerging areas that may not yet attract mainstream funding. Confirm the full requirements in the official notice before applying.
The current listing shows grants generally range from approximately $100,000 to $400,000. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Alfred P. Sloan Foundation Exploratory Grantmaking in Technology: AI in Science and Research Automation are due December 31, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Alfred P. Sloan Foundation Exploratory Grantmaking in Technology: AI in Science and Research Automation is funded by Alfred P. Sloan Foundation. 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 Sloan Foundation's exploratory grantmaking in Technology supports the development and adoption of AI tools that accelerate scientific research and automate aspects of the scientific process. Funded scope includes foundation models for science (chemistry, biology, materials, physics), AI lab automation and self-driving laboratories, AI-driven literature review and synthesis tools, machine learning for experimental design, scientific reasoning and hypothesis generation in LLMs, and infrastructure for open scientific AI. The exploratory program identifies emerging sectors, tools, and methods with high potential that may not yet attract mainstream funding, prioritizing interdisciplinary risk-taking work.
Human-AI Interaction Research Grants for Multidisciplinary Research and Prototyping is sponsored by Alfred P. Sloan Foundation. This grant funds multidisciplinary research on human-AI interaction—how people interact with, are affected by, and can benefit from artificial intelligence systems—as well as prototyping of novel uses of AI systems that move research insights into practice.
The K-12 AI Infrastructure Program, run by Digital Promise with Learning Data Insights, DrivenData, Georgetown University's Massive Data Institute and Catalyst @ Penn GSE and funded by the Gates Foundation, released this request for proposals on 7 October 2026. It will fund up to two awards of up to $600,000 each from a $1 million pool. Grantees will build an openly licensed package of tools, workflows and documentation, such as a reference architecture, harness or starter kit, that helps developers explore, test and integrate education-specific digital public goods into AI-enabled formative assessment products. Phase 1 focuses on coordination between teachers and classroom AI tools, giving teachers more visibility into and control over AI. Proposals must cover at least four teacher-AI coordination tasks, engage at least three AI developers and include a classroom demonstration, and most funded work must serve third-party developers rather than end users. Code must be released under MIT or Apache 2.0 and datasets under CC-BY-4.0. The grant period is 18 months in three phases of about six months, starting 1 February 2027. This is a separate, narrower solicitation from the program's March 2026 first grant cycle. Proposals are due 20 November 2026 at 11:59 p.m. Anywhere on Earth.
The K-12 AI Infrastructure Program released this request for proposals on October 7, 2026. It funds an openly licensed package of tools, workflows and documentation, such as a harness, reference architecture or starter kit, that helps developers build education-specific public goods into AI-enabled formative assessment products. The aim is to coordinate the work of teachers and AI tools so teachers can see, control and monitor the AI used in their classrooms. Proposals must name at least four tasks that improve teacher-AI coordination, engage at least three AI developers and include a classroom demonstration application. Most of the effort must serve third-party developers rather than end users. Code must be MIT or Apache 2.0 licensed and datasets CC-BY-4.0. Up to two awards of up to $600,000 each will be made from a $1 million pool. Projects run 18 months in three phases starting February 1, 2027. Proposals are due November 20, 2026 at 11:59 p.m. Anywhere on Earth. This is a separate round from the program's earlier formative assessment, EDU AI and benchmarks RFPs.
The Tarbell Fellowship is a full-time, hybrid program run by the Tarbell Center for AI Journalism that trains journalists to cover artificial intelligence, including AI safety, governance and accountability. Applications for the 2027-28 cohort close on 22 November 2026. A work test follows in December 2026 to January 2027, interviews run from January to March 2027, and fellows are selected in late March 2027. The program opens with a remote AI Journalism Fundamentals course from 7 June to 6 August 2027, followed by an in-person summit planned for 16-20 August 2027. Fellows are then placed as embedded reporters at partner newsrooms from September 2027 to May 2028, with a possible one-year extension. Fellows earn $75,000 to $120,000, and senior fellows with seven or more years of experience earn $115,000 to $135,000. Partner newsrooms set the assignments. Applicants submit one to three writing samples of no more than 4,500 words in total, and AI-generated text is not allowed.