Org profile: sourced & linked
Organization Profile
Schmidt Sciences
Schmidt Sciences is a philanthropic nonprofit founded by Eric and Wendy Schmidt that funds hypothesis-driven scientific research through targeted grant programs and virtual institutes, with a strong focus on AI safety and advanced computing alongside other scientific domains. Its Science of Trustworthy AI program funds technical research to understand, predict, and control risks from advanced AI systems, in two funding tiers (up to $1M, and $1M–$5M+ over one to three years). Schmidt Sciences proactively solicits proposals through open RFPs and does not accept unsolicited applications.1,2,3
Programs
4 programs on fileMulti-Agent Safety (Scaling AI Safety for a Multi-Agent World)
0 grants tracked
2026 call: closed, closes 2026-08-08
Schmidt Sciences — Science of Trustworthy AI
0 grants tracked
2026 Science of Trustworthy AI RFP: closed, closes 2026-05-17
Schmidt Sciences AI Interpretability RFP
0 grants tracked
AI Interpretability RFP: closed, closes 2026-05-26
Schmidt Sciences RFP for AI-at-Work Field Experiments
0 grants tracked
2026 research agenda: closed, closes 2026-04-10
JanFebMarAprMayJunJulAugSepOctNovDec◆ Today
Multi-Agent Safety (Scaling AI Safety for a Multi-Agent World)2026 call: closed, closes 2026-08-08
0 grants tracked
Schmidt Sciences — Science of Trustworthy AI2026 Science of Trustworthy AI RFP: closed, closes 2026-05-17
0 grants tracked
Schmidt Sciences AI Interpretability RFPAI Interpretability RFP: closed, closes 2026-05-26
0 grants tracked
Schmidt Sciences RFP for AI-at-Work Field Experiments2026 research agenda: closed, closes 2026-04-10
0 grants tracked
Awards
33 on fileShowing 26-33 of 33, newest dated evidence first
RecipientProgramAmountDateEvidence
- Song — Exploring AI Safety in Free-Form, Evolutionary Multi-Agent SystemsProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Thilo Hagendorff — Investigating Hawthorne Effects in Large Reasoning ModelsProgramScience of Trustworthy AI (Inference-Time Compute)Amount–Date–
- Xiao — Evaluating and Defending Multimodal Computer-Use Agents under Adversarial AttacksProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Yarin Gal — Tracing and Eliminating Harmful Capabilities Across Model GenerationsProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Yoshua Bengio — LLM-Derived Guardrail for Frontier Models as a Step Towards a Cautious Scientist AIProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Ziang Xiao — BenchCraft: An AI-powered Toolkit to Create Valid and Efficient BenchmarksProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Zico Kolter — Understanding the Mechanism of Adversarial Transfer Across AI ModelsProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
- Zilberstein — Unlocking Multi-Agent System Safety with Dynamic Islands of TrustProgramScience of Trustworthy AI (Understanding Safety in AI Systems)Amount–Date–
4
Programs
33
Awards
33
Grantees
–
Known USD
0
Live rounds
no open or announced rounds on file
Active
Status
Focus Areas
AI safety, AI alignment, interpretability, AI evaluation science, frontier model risk, trustworthy AI, AI oversight, multi-agent risk.
Typical sizeTier 1: up to $1M; Tier 2: $1M–$5M+, each over 1–3 years (2026 Science of Trustworthy AI RFP)
CadenceRFP-driven open calls; does not accept unsolicited proposals