Currently 15 active ai and ai safety grants, fellowships and residencies open to applicants in the US. Hand-curated and updated weekly. Almost every entry is funded; a few notable unpaid open calls and festival submissions are included as clearly flagged exceptions. Browse the list below, or use the interactive desk for filtering and shortlisting.
Subscribe: RSS feed · Calendar (.ics)
The ILIAD Fellowship is a 3-month mentored research fellowship producing concrete outputs in applied-mathematical AI alignment research, distinct from ILIAD's four-week taught Intensive. Fellows work in person in London or the SF Bay Area with a USD 6,000 per month travel-and-housing allowance. ELIGIBILITY: primarily PhD and postdoc researchers in mathematics, theoretical physics, theoretical computer science or related fields, though a degree is not a hard requirement given substantial research experience; limited remote flexibility. DEADLINES: 21 September 2026 for the November cohort (2 November 2026 to 5 February 2027); 19 October 2026 for the December cohort (1 December 2026 to 5 March 2027). A single common application at iliad.ac/apply covers the Fellowship and the Intensive.
Humanity AI, an initiative of ten leading philanthropies, opens a USD 10 million call for community-led initiatives that shape how AI affects people's lives. ISSUE AREAS: Education (student and educator-centered work shaping AI's educational impact); Labor and Economy (worker-led efforts to ensure AI enhances rather than replaces employment); and Humanities, Arts, and Culture (artist and creator-focused work protecting cultural contributions). ELIGIBLE APPROACHES: shaping the rules for AI governance and deployment; building AI controlled by communities rather than corporations; and challenging misaligned AI deployments. Community-led means the affected community defines the goals and shapes the approach. Priority goes to open-weight and open-source AI models over proprietary ones. OUT OF SCOPE: AI literacy training, AI adoption promotion, and research-only work. GRANTS: three tiers from USD 75,000 to 1,000,000, up to three years. ELIGIBILITY: US-based 501(c)(3) organizations as lead applicants; individuals via fiscal sponsors or collaborations; Tribal governments treated as States under IRC Section 7871; for-profit entities only as collaborators, not leads; all proposals must serve US-based communities. TIMELINE: launched 10 September 2026; applicant webinar 14 September 2026; initial applications due 21 October 2026 at 4:59pm PT; finalists notified December 2026; awards announced early spring 2027. Apply via Submittable; an organizational readiness tool on the site helps assess eligibility first.
Umbrella request for proposals for ambitious AI-first projects that make the transition to capable AI go well and use it to unlock science. Three connected layers, each with its own detailed call: I. Local Compute (compute that individuals or communities physically own and control); II. Coordination and Accountability (supercollaboration and decentralized alignment, human empowerment, AI insurance and open governance); III. AI-First Science: Bio, Neuro, Nano (automated nanotechnology, whole-brain emulation, replacement, enhancement, biostasis). AI-first means AI is the primary engine of progress, not tapped onto an existing research program; strong proposals identify narrow bottlenecks and propose something that can be built, tested or measured. Selected projects receive grant funding, private local compute, workspace at the San Francisco or Berlin AI Nodes, travel-paid field-building events and access to Foresight's advisors and scientific network. ELIGIBILITY: individuals, teams, and nonprofit or for-profit organisations worldwide (for-profits must justify their need for grant funding); applicants who want to be active in-person contributors at the Nodes are strongly prioritised. Grants typically $30,000 to $100,000, smaller for the Human Empowerment and AI Insurance & Open Governance areas and higher for the rest. Review takes about three months after the deadline. Deadline 31 October 2026, 23:59 PDT.
The MATS Residency, announced in August 2026 as a new track alongside the seasonal MATS fellowship, funds 6 to 24 months of high-independence AI safety research for experienced researchers, whether already in AI safety or moving in from adjacent fields. COMPENSATION: USD 155,000 to 285,000 per year gross depending on location, seniority and experience, plus insurance, retirement plan, PTO (17 days US / 20 days UK), conference funding, catered meals, and up to USD 25,000 in relocation support. ELIGIBILITY: at least one substantial piece of research-caliber work; credentials are not required. Full-time (part-time case by case for academics on sabbatical), in person at MATS offices in Berkeley, London, or Washington DC, with visa support where required. TIMELINE: the Winter 2027 intake window runs 25 August to 31 October 2026 (AoE), with decisions by end of November and interviews plus a paid work test in the first week of December; three intake windows per year.
Track I of Foresight Institute's AI for Science & Safety Nodes RFP funds building and scaling local compute setups that individuals or communities physically own and control. With five companies holding 71 percent of the world's AI compute, researchers relying on APIs and rented compute face data exposure, steep price increases and the risk of losing access altogether; open models are ready for serious science and safety work, but the ecosystem lacks sovereign and secure compute infrastructure. LOOKING FOR: local compute clusters in different sizes and configurations that are easy to set up and run across varied connectivity and electricity environments; blueprints for easy yet secure cluster management; models for bringing down cost, like selling idle compute or connecting to community clusters; ideally a business case for building, selling and distributing such clusters at scale. EXAMPLE DELIVERABLES: a prototype AI cluster an average person can deploy at home, software that runs a node without expert knowledge, economic models showing how the hardware pays for itself, a pilot deployment for individuals or communities. Selected projects receive grant funding, private local compute, workspace at the San Francisco or Berlin AI Nodes, travel-paid field-building events and access to Foresight's advisors and network; in-person contributors at the Nodes are strongly prioritised. Individuals, teams, and nonprofit or for-profit organisations worldwide may apply (for-profits must justify their need for grant funding). Deadline 31 October 2026, 23:59 PDT.
Track II of Foresight Institute's AI for Science & Safety Nodes RFP funds ways for increasingly capable AI systems to coordinate with each other, the people using them, and the wider world, without handing power to a single model, lab or government. THREE FOCUS AREAS: (1) Supercollaboration and decentralized alignment: coordination and credit-assignment protocols, tooling for massive human-AI collectives, incentive designs robust to gaming, mutual monitoring and cross-checking among agents, scalable verification, and open coordination protocols built on boundaries as Schelling points for multi-agent coordination. (2) Human Empowerment: evidence, decision rules and working tools for when human control genuinely empowers people versus when AI delegation is preferable, including a 'when to defer control' framework and mechanisms to detect and fix hollow oversight. (3) AI Insurance and Open Governance: building a middle layer between lab self-governance and government regulation, such as ways for insurers to judge and price frontier-lab risk, independent incident reporting and assessment that does not leak lab secrets, and mechanisms like developer mutuals, catastrophe bonds or liability for near-misses. Selected projects receive grant funding, private local compute, workspace at the San Francisco or Berlin AI Nodes, travel-paid field-building events and access to Foresight's advisors and network; in-person contributors at the Nodes are strongly prioritised. Individuals, teams, and nonprofit or for-profit organisations worldwide may apply (for-profits must justify their need for grant funding). Deadline 31 October 2026, 23:59 PDT.
Track III of Foresight Institute's AI for Science & Safety Nodes RFP funds AI-first science in bio, neuro and nano: work that asks what important science is stuck, what it is actually stuck on, and whether we can build the thing that removes that constraint. THREE FOCUS AREAS: (1) Automated nanotechnology: AI methods for nanoscale design, simulation and assembly, closed-loop fabrication and characterization tools, credible application pathways from toy problems to medicine, environment and bottom-up production, and defensive applications and safety frameworks. (2) Whole-brain emulation: cheaper and faster brain mapping and preservation, bringing down the cost of connectomics through better imaging or cheaper proofreading, lo-fi emulation pathways that predict organism behavior from behavioral and neural data, and shorter experimental feedback loops in neurobiology. (3) Replacement, Enhancement, Biostasis: longevity work including tissue engineering, organ synthesis, 3D bioprinting and progressive replacement strategies; reversible biostasis for organs and full humans with improved preservation and revival protocols and organ banking; and datasets for independently testing genetic predictors, gene editing and better measures of aging. Selected projects receive grant funding, private local compute, workspace at the San Francisco or Berlin AI Nodes, travel-paid field-building events and access to Foresight's advisors and network; in-person contributors at the Nodes are strongly prioritised. Individuals, teams, and nonprofit or for-profit organisations worldwide may apply (for-profits must justify their need for grant funding). Deadline 31 October 2026, 23:59 PDT.
The AAAS Science & Technology Policy Fellowships place scientists and engineers inside US federal agencies, congressional offices and the judicial branch for a year of hands-on policymaking, contributing technical knowledge and analytical skills to the federal policy process. AI, data and computing policy placements are among the largest tracks, and AAAS runs a dedicated AI legislative branch cohort that places AI experts in congressional offices at GS-12 Step 10 on the DC locality scale. ELIGIBILITY: US citizens holding a PhD or equivalent doctoral degree in any science or engineering field, or a master's degree in engineering plus three years of post-degree professional experience; some tracks accept a bachelor's plus five years. Relevant expertise includes AI, machine learning, computer science, robotics and data science. Fellows must reside in DC, Maryland or northern Virginia during the fellowship year. TIMELINE: the application portal opens 1 August 2026 and closes 1 November 2026 at 11:59pm ET, with eligibility notification in late November, interview notification January to February 2027, semi-finalist interviews in March, placement offers by early May, and the fellowship year running 1 September 2027 to 31 August 2028. Apply through fellowshipapp.aaas.org.
The Institute for Law & AI's US Summer Fellowship is a paid research fellowship at the leading edge of US AI law and policy for law students, professionals, and academics, including the Summer Institute on Law and AI in Washington DC and mentorship from LawAI research staff. FUNDING: USD 2,000 per week, a USD 10,000 relocation/housing stipend for DC-based fellows, covered flights, accommodation and meals for the Convening Week, and potentially higher subsidies for exceptional candidates. ELIGIBILITY: a strong grasp of US legal principles applicable to AI regulation via formal US legal study (incoming 1L and up) or comparable professional experience; full-time commitment 14 June to 20 August 2027; valid US work authorization required (visa sponsorship possible but not guaranteed). The application takes about 20 minutes. DEADLINE: 29 January 2027, 11:59PM ET.
Robot foundation models (pi-zero, OpenVLA, GR00T and others) are approaching widespread deployment on the back of more than USD 18 billion in funding, and almost nobody is working on their safety. The Physical AI Safety Institute, a new nonprofit founded by Bear Haon and Kaylene Stocking and seeded by a grant from BlueDot Impact, describes itself as a capacity-building organisation growing the community that develops techniques to interpret, align and control robot foundation models. Its research fellowship runs in 12-week cohorts: each fellow works within a stream led by a mentor on a concrete problem in physical AI safety, with mentors drawn from researchers with track records in robot foundation models, mechanistic interpretability, safe control or adversarial robustness for embodied systems. Each cohort ends with a research symposium where fellows present their work. STREAMS: mechanistic interpretability (sparse autoencoders and activation patching for VLA and WAM architectures); adversarial robustness (jailbreaking and prompt injection in the embodied action space); runtime monitoring (detecting when a policy operates outside its competence envelope); sim-to-real safety transfer (do safety behaviours survive deployment on physical hardware); and robot security (cyberattack vectors, data poisoning and supply chain for deployed robot models). WHO SHOULD APPLY: researchers with strong technical foundations in robotics or machine learning and a demonstrated interest in safety; prior safety experience is not required. PROCESS: this stage is an expression of interest, not a full application. The form takes about two minutes and asks you to pick your stream and preferred cohort dates; concrete details including stipend figures and application deadlines are shared through that channel, and neither is published on the site as of listing. PAISI also publishes seven free curriculum modules running from classical robot safety through VLA interpretability, adversarial robustness and runtime monitoring to deployment evaluation, plus a white paper, The Case for Physical AI Safety, at paisi.ai/the-case-for-physical-ai-safety. Contact: bear@paisi.ai.
The Institute for Advanced Study is seeking a 2026-27 Civic Science Fellow to advance understanding of the social, democratic and scientific implications of artificial intelligence. The full-time, 18-month position is based in the Science, Technology, and Social Values Lab led by Harold F. Linder Professor of Social Science Alondra Nelson. Working closely with Professor Nelson and Lab members, the Fellow contributes to research and policy analysis and to scholarly and public-facing publications, and supports multidisciplinary, multisector initiatives at the intersection of AI, science and governance. DUTIES (75% Lab work): conduct original research on the Lab's AI-and-society agenda; synthesize scholarship on the social implications of AI, sociotechnical approaches to AI governance and the epistemological implications of AI in research; contribute policy research on governance mechanisms that strengthen democratic institutions; help organize convenings and working groups; collaborate on manuscripts, reports and grant proposals; support editorial development of publications; and develop public-facing essays, policy briefs and digital materials. The remaining 25% supports the Fellow's own independent research, network-building and full participation in the intellectual life of IAS. MINIMUM QUALIFICATIONS: a PhD in the social sciences, sciences or humanities; a strong record of scholarly research, writing and publication on the social implications of science and technology or related fields; and exceptional writing and editing skills for both academic and non-academic audiences. Preferred: specialization in science and technology studies, science and technology policy, organizational studies or qualitative methods, and demonstrated engagement with AI governance and technology policy debates. Apply with a cover letter and resume via the IAS/Paylocity posting.
The CHAI Research Fellowship trains highly qualified postdoctoral researchers to advance beneficial AI, working with CHAI faculty Stuart Russell, Pieter Abbeel and Anca Dragan and collaborating with affiliate faculty at Berkeley AI Research and beyond. Fellows have broad freedom to pursue novel research toward provably beneficial AI systems in areas such as reasoning, decision making, learning, multi-agent systems and philosophical foundations, using probability theory, game theory and control theory. Current topics of interest include theoretical foundations of intelligent agent architecture, expressive formal languages for probability models (including probabilistic programming), decision making over long time scales, cumulative lifelong learning, human-in-the-loop planning and reinforcement learning, human-robot interaction, the structure of human preferences, acting on behalf of multiple humans, robust cooperation in heterogeneous multi-agent systems, and mechanism design for human-machine systems. Fellows may also lead collaborations, advise junior researchers, and teach. QUALIFICATIONS: a PhD (or about to be obtained) in a relevant technical discipline (computer science, statistics, mathematics, or theoretical economics) and a record of high-quality published research; prior work on the AI control problem is not required. International applicants are eligible (visa sponsorship provided). TO APPLY: submit via the CHAI application form a resume, a one-page statement of interest describing the research you would like to undertake, and the names and emails of two academic referees. Start date is flexible and applications are reviewed on a rolling basis (no fixed deadline). General enquiries: chai-info@berkeley.edu.
The Good Life Residents Program is a six-month Roosevelt Institute initiative that develops new leaders and elevates bold ideas across six economic policy priorities under its Good Life Agenda. Each topic area hosts a cohort of 3 to 4 residents plus 1 to 2 senior Topic Advisors (academics, policy leaders, organizers or government practitioners) who provide strategic and intellectual mentorship and moderate the closing event. Residents write a roughly 1,500-word original policy essay advancing a people-centered policy vision against a topic-specific prompt, take part in structured dialogue with peers, Topic Advisors and Roosevelt Think Tank directors, help prepare and appear at a culminating public event, contribute to press opportunities such as op-eds and reporter calls where applicable, and act as ambassadors for the Good Life Agenda in their professional and public networks. The current round, the AI and Finance Residents Program, is run in partnership with Data & Society and asks for bold ideas on how to shape, redirect, interrupt or make more visible and contestable the flows of capital into generative AI. Framing: breakneck investment in generative AI technology and infrastructure is distorting the stock market, profit measures, bond issuance, the pace and composition of growth, job creation and trade policy, with seven tech companies accounting for more than a third of S&P 500 market capitalisation and complex, sometimes circular financial arrangements obscuring risk. Suggested lines of inquiry include what government interventions could improve public oversight, risk allocation and direction-setting in private markets; how other investments could be coordinated and scaled if AI spending is crowding them out; what role public spending or new institutions could play in catalysing technology R&D designed to support workers, sustainability and supply chains; what democratic input mechanisms would keep state influence over capital flows less vulnerable to corruption; and how federal AI policy should address public hostility to data centre investments alongside national security and competitiveness. Compensation is USD 3,000 plus travel and accommodation for the culminating event. FLAG: Roosevelt does not publish an application deadline for the AI and Finance round on the programme page, and earlier rounds (Social Security financing, Federal Reserve powers, housing) each ran their own short application window. Check the Formstack application form linked from the programme page for the current closing date before applying.
The ILIAD Intensive is a four-week, full-time, in-person program for mathematically strong researchers interested in foundational AI alignment, running in London (at LISA) and in Berkeley. It runs five days a week, 10am to 6pm, in cohorts of 15 to 30 participants. CURRICULUM, across five clusters: Alignment (decomposing the alignment problem, pretraining, post-training and deployment, reward learning); Learning (deep learning theory, singular learning theory, training dynamics); Abstractions, Representations and Interpretability (mechanistic interpretability, natural latents); Agency (reinforcement learning, decision theory, agent foundations); and Safety Guarantees (debate, steganography, the limits of interpretability). MONEY: no tuition is charged. Each participant receives a USD 5,000 travel and housing allowance, office space at the venue, and lunch and dinner five days a week. Participants book and pay for their own travel and accommodation out of the allowance. ELIGIBILITY: a strong mathematical background, typically graduate-level study or a completed degree in mathematics, physics or theoretical computer science, though mathematical maturity is weighted more heavily than specific credentials. Research experience, general competence and motivation are also assessed. Prior machine learning or alignment experience is not required. DEADLINE: no fixed closing date is published. A single application covers several upcoming programs and applicants indicate their preferred dates and locations; applications are being accepted for the October 2026 and November 2026 cohorts. HOW TO APPLY: through the application portal at iliad.ac/apply. Questions to contact@iliad.ac.
The Anthropic Fellows Program is a four-month, fully funded research fellowship with direct mentorship from Anthropic researchers. Fellows work on empirical projects aligned with Anthropic's research priorities using external infrastructure, aiming to produce public outputs such as papers. Five workstreams: AI Safety, AI Security, ML Systems and Performance, Reinforcement Learning, and Economics and Policy; safety topics include scalable oversight, adversarial robustness, mechanistic interpretability, and model organisms. FUNDING: a weekly stipend of USD 3,850 (GBP 2,310 / CAD 4,300), around USD 15,000 per month in compute funding, and other research expenses. ELIGIBILITY: fluent Python; available full-time for four months; strong technical background in computer science, mathematics, or physics; work authorization in the US, UK, or Canada (no visa sponsorship). Locations: San Francisco, London, Ontario, or remote within those countries. APPLICATION: rolling, via the Constellation portal; the process includes an initial application, reference checks, technical assessments, interviews, and a research discussion. The next cohort is expected to start in January 2027, so apply well before the end of 2026.