AIXI Labs: Research Fellowship (rolling, quarterly rounds)

About

Organisation: AIXI Labs Location: Fully remote, open worldwide; fellows may also work from the organisation's London base in the United Kingdom. Award: GBP 2,000 to GBP 3,500 per month stipend, plus a compute budget for machine-learning work. Free to apply. Duration: Roughly one quarter (about 3 months) per fellowship. Quarterly rounds, rolling applications. Renewal possible in exceptional cases. Deadline: Rolling / undated 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. Open call details Want to see more grants? Visit The Grant Desk (https://www.artificialnouveau.com/smalltools/grants/).

Who can apply

See original listing for eligibility details.