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The Pivotal Research Fellowship is a nine-week AI safety research program (June 29 to August 28, 2026) based at the London Initiative for Safe AI (LISA), with optional extensions of up to six months for strong projects. Fellows receive a GBP 6,000-8,000 stipend, GBP 2,000 housing allowance for non-London residents, London travel coverage, compute resources, and weekday meals.
The program offers weekly one-on-one mentorship with established AI safety researchers, dedicated in-person workspace at LISA, research management support, workshops, and speaker sessions. The selection process involves a written application, video interview, mentor-specific work task, and personal interview.
Pivotal Research reports that 70 to 90 percent of fellows who applied received extensions in recent cohorts, indicating strong support for continued research development. The fellowship accepts researchers from diverse backgrounds including ML, philosophy, policy, physics, and biology.
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Or search similar grants →According to the current listing, eligibility includes: Anyone 18 or older committed to ensuring AI develops safely. Backgrounds in machine learning, philosophy, policy, physics, biology, or related fields are considered. No specific academic degree requirements. Must be able to participate in-person in London for the full nine weeks. Confirm the full requirements in the official notice before applying.
The current listing shows GBP 6,000 to GBP 8,000 stipend (approximately $7,500 to $10,000 USD). GBP 2,000 housing allowance for non-London residents. Travel to London and compute resources covered. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was May 3, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Pivotal Research Fellowship for AI Safety in London 2026 is funded by Pivotal Research Ltd. 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 Halcyon Africa Innovation in Agriculture and Food Security Accelerator supports early-stage, impact-driven ventures across Sub-Saharan Africa that are strengthening agriculture and food systems through market-based solutions. The 2027 cohort is open for applications until 23 October 2026. Technology is explicitly central to the scope: the programme welcomes tech-enabled agriculture and food security solutions across ten priority sectors, including agricultural data platforms, digital extension services, precision agriculture tools and agri-fintech innovations, all areas where AI and machine learning are typically the core of a competitive product. Each selected venture receives a 10,000 US dollar equity-free stipend and 10,000 dollars in Amazon Web Services credits, together with access to Halcyon's community of more than 650 founders, professional advisory support, expert-led workshops covering leadership development, capital strategy and product-market fit, and investor networking. The format is hybrid, combining virtual sessions with in-person residencies in Accra, Ghana and Nairobi, Kenya. What distinguishes this from most AI-for-agriculture funding is the applicant profile: it targets commercial ventures with working products and demonstrated traction rather than research teams, requiring paid-pilot or post-revenue stage with a working minimum viable product. For African AgTech founders building AI-driven advisory, monitoring or decision-support tools who have passed the prototype stage and need capital strategy support and investor access more than research funding, this is a well-matched and currently open opportunity.
Foresight's AI for Science and Safety Nodes RFP is a small-cheque, high-variance programme aimed at work that conventional funders will not touch, and it is one of the few AI safety calls verifiably open with a future deadline of 31 October 2026. The framing joins two problems: ensuring a safe transition to highly capable AI, and using AI to unlock scientific breakthroughs. Proposals sit in one of three layers. Local compute covers community-owned and controlled computational infrastructure - an explicitly decentralist counterweight to frontier-lab concentration. Coordination and accountability covers human-AI interaction, supercollaboration and AI risk assessment mechanisms. AI-first science covers automated nanotechnology, whole-brain emulation and frontier biotechnology. The single most important screening criterion is stated plainly: Foresight wants projects where AI is the primary engine of progress, not projects where AI is, in its words, tapped onto an existing research program - so an established lab adding a machine learning component to ongoing work is the archetype of what gets rejected. Evaluation weights alignment with a focus area, impact on AI existential risk reduction, feasibility within short AGI timelines, execution capability, and high-risk high-reward potential. Two conditions are non-negotiable: all outputs must be open-sourced, and applicants must commit to active participation at Foresight's San Francisco or Berlin nodes, which makes this poorly suited to a purely remote team. Application is a single Airtable form with a roughly three-month review.
The Foresight Institute's AI for Science and Safety Nodes RFP funds work across three layers with a deadline of 31 October 2026 at 23:59 PDT. The Local Compute layer supports community-owned compute infrastructure. The Coordination and Accountability layer covers supercollaboration, decentralised alignment, human empowerment, and AI insurance and open governance. The AI-First Science layer covers nanotechnology, neurotechnology and longevity biotechnology. Awards typically run 30,000 to 100,000 US dollars, with larger amounts possible for the right project and smaller awards in the human empowerment and AI insurance areas. What distinguishes this programme from conventional AI safety funding is that money is only part of the offer: recipients receive office space at Foresight's San Francisco and Berlin hubs, access to a private compute cluster, travel-paid field-building events, and access to Foresight's advisors and scientific network, and the institute states it strongly prioritises applicants who want to be active, in-person contributors. It is therefore better understood as a residency-style node programme than as a grant competition, and applicants unwilling or unable to be physically present at a hub are at a structural disadvantage regardless of proposal quality. Priority goes to projects delivering concrete milestones and deliverables in the next one to three years, both short-term and longer projects are funded, and open-sourcing of code, data and outputs is mandatory. Application is through an online Airtable form, followed by in-house review for fit and quality, referral of strong submissions to technical advisors, possible written questions or calls, and a review timeline of approximately three months after the deadline. Due diligence includes background verification and budget documentation.