Currently 6 active ai and ai safety grants, fellowships and residencies open to applicants in the UK. 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.
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The Open Data Institute, the London non-profit founded by Tim Berners-Lee and Nigel Shadbolt, is hiring a Researcher (AI and quantitative) in its Research and Development team. The role focuses on data-centric AI: benchmark creation and model evaluation, and improving the AI readiness of existing and emerging data infrastructures. DAY TO DAY: running rigorous experiments to evaluate model performance across technical metrics; leading work packages covering corpus construction, ground-truth curation, task design, evaluation harnesses, statistical analysis and benchmarking reproducibility; assessing public sector and government datasets for AI-readiness using ODI frameworks; authoring peer-reviewed papers, technical annexes, reproducible code repositories, blog posts and policy briefings; plus desk reviews, literature reviews, stakeholder mapping, surveys and interviews on data, AI and technology topics. WHO THEY WANT: practical experience in data-centric AI methodologies including benchmark building and dataset quality assurance; deep applied knowledge of LLMs, RAG and agentic frameworks; experience with evaluation protocols, harness design and comparative benchmarking across major open and closed-source model families; proficiency in statistical modelling and ML workflows; mixed qualitative and quantitative research skills; understanding of open science and FAIR principles and of GDPR implications for research. Desirable: a track record of commissioned research or policy briefings for tech organisations, government bodies or foundations, and knowledge of current debates in the data and open culture movements, including the collection and use of data by AI systems. TO APPLY: upload a CV, a cover letter, and work samples including links (GitHub, Hugging Face) to previous AI projects relevant to the position. Closing date Friday 9 October 2026. Questions to jobs@theodi.org.
The Institute for Law & AI's Winter Research Fellowship (EU Law) is a 10-week full-time paid research fellowship for lawyers who want to deepen their understanding of AI and law and contribute to the field, with close support and mentorship from LawAI staff. Previous Seasonal Research Fellows have gone on to legal and policy roles in the European AI Office, leading AI companies, academia and think tanks, including LawAI itself. FUNDING: a GBP 1,000 weekly stipend plus a GBP 7,000 relocation and housing payment; fellows work from LawAI's Cambridge, UK office, with remote candidates considered in exceptional circumstances. ELIGIBILITY: open to graduate law students, professionals and academics with diverse skill sets, experience levels and degrees of knowledge in AI law and policy. Fellowship runs 1 February to 9 April 2027. Applications are considered on a rolling basis as received, so apply early. DEADLINE: 12 October 2026.
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.
AIXI Labs is a small London-based non-profit doing AI safety research grounded in algorithmic information theory. Its stated position is that most AI research today is either mathematically clean but narrow, or practical but too opaque for rigorous safety analysis; the lab targets a third category, methods general enough to describe powerful agents and provable enough to support real safety claims, using AIXI (the theoretical model of unbounded artificial superintelligence) and then porting the strongest of those ideas to modern LLM-based agents. The fellowship is a quarterly, rolling programme for researchers who want to work on this agenda under close mentorship from the core team: Cole Wyeth (Founder and Executive Director), Marcus Hutter (Research Director) and Aram Ebtekar (Founding Research Scientist). Fellows pursue a focused research project over roughly a quarter and receive a monthly stipend plus a compute budget for machine-learning work. The fellowship is fully remote, so fellows may work from anywhere in the world or from the London base. RESPONSIBILITIES: pursue a self-directed research project aligned with the lab's algorithmic-information-theoretic approach to AI safety, spanning anything from foundational theory to empirical tests with LLM-based agents; shape the project direction around your own strengths and interests, as the lab supports a range of work within this framework; and contribute papers, blog posts or other written output communicating results to the broader AI safety and ML research communities. MINIMUM QUALIFICATIONS: a research background at the level of a current PhD student (for primarily empirical projects, a master's-level command of the relevant mathematics paired with substantial industry or applied research experience can also qualify); solid grounding in probability, statistics, information theory and reinforcement learning, sufficient to engage seriously with AIXI-style theoretical models (prior expertise in algorithmic information theory or AIXI is NOT required); strong verbal and written communication skills; genuine motivation to reduce existential risk from advanced AI and enthusiasm for the lab's kind of work. PREFERRED QUALIFICATIONS: publications at top ML, AI or theory venues such as NeurIPS, ICML, ICLR, ALT or COLT, though the lab values the strength of your best work over volume; background in algorithmic information theory, computability theory, learning theory or related theoretical computer science; experience fine-tuning, evaluating or red-teaming LLM-based and/or RL agents; prior engagement with the UAI/AIXI community or related fields, including members of the lab's online reading groups. APPLICATIONS are reviewed on a rolling basis and previous applicants remain eligible for later rounds.
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.