AIXI Labs Research Fellowship Scholarship 2026 in UK

Overview

The AIXI Labs Research Fellowship is a quarterly, rolling programme designed for global researchers to investigate AI safety grounded in algorithmic information theory. Participants pursue targeted research projects alongside mentorship from the core team at AIXI Labs, a London-based non-profit organization. The fellowship can be completed fully remotely from anywhere worldwide or optionally from the London base.

Benefits

Monthly stipend ranging between £2,000 and £3,500.
Dedicated compute budget dedicated to machine learning experiments.
Direct mentorship from core team members including Cole Wyeth, Marcus Hutter, and Aram Ebtekar.
Opportunities to publish papers, blog posts, and share community outputs.

Eligibility

Possess a research background equivalent to a current PhD student level, or hold a master’s-level command of mathematics accompanied by substantial industry or applied research experience.
Demonstrate a solid grounding in probability, statistics, information theory, and reinforcement learning.
Show strong verbal and written communication skills alongside a genuine motivation to mitigate existential risks from advanced artificial intelligence.
Preferred qualifications include top-tier venue publications, experience in algorithmic information theory or related theoretical computer science, and familiarity with fine-tuning or red-teaming LLM and reinforcement learning agents.

How to Apply

Candidates must prepare a research proposal that aligns with the algorithmic-information-theoretic approach utilized by AIXI Labs. Submissions are processed online through the official application portal.

Deadline

Applications are reviewed on a rolling basis with no fixed deadline.

Overview

Eligibility

Possess a research background equivalent to a current PhD student level, or hold a master’s-level command of mathematics accompanied by substantial industry or applied research experience.

Demonstrate a solid grounding in probability, statistics, information theory, and reinforcement learning.

Show strong verbal and written communication skills alongside a genuine motivation to mitigate existential risks from advanced artificial intelligence.

Preferred qualifications include top-tier venue publications, experience in algorithmic information theory or related theoretical computer science, and familiarity with fine-tuning or red-teaming LLM and reinforcement learning agents.