Currently 3 active fellowships open to applicants in the UK, across AI, arts, film, journalism, research, tech and cross-disciplinary practice. 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 UAL AKO Storytelling Institute, with the Power of Pop Fund, is recruiting six Storytelling Research Fellows to run independent research projects on how storytelling in popular culture shapes attitudes, behaviour and public discourse. Fellows work across media including television, film, gaming, podcasts and digital culture, are supported by the Institute's Head of Research and a peer cohort, and produce actionable findings for creative practitioners, funders and social-impact organisations, presented at a closing public symposium. ELIGIBILITY: experienced researchers with a PhD or equivalent research expertise gained academically, independently or through professional practice, with a track record of delivering high-quality research and working with external partners. Practice-based and non-academic researchers are explicitly in scope. APPLICATION: CV, record of publications, a research proposal of 1,000 to 1,200 words, and a supporting statement including at least one example of a research project you designed and delivered. Applications via the UAL jobs portal; closes 11 September 2026.
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.