Impact Academy’s Global AI Safety Fellowship is a 3-6 month fully-funded research program for exceptional STEM talent to work with the world’s leading AI safety organisations on advancing the safe and beneficial development of AI.
The program select Fellows from around the world for a 3-6 month placement with program partners. After an initial application, candidates will be invited to participate in a rigorous and purpose-driven selection process that lasts 4 to 6 weeks. The aim is to select a cohort of technically skilled individuals with a knack for working on complex problems.
Some of the partners are the Center for Human Compatible AI (CHAI) at UC Berkeley, Conjecture, FAR.AI, the Mila–Quebec AI Institute, and the UK AI Safety Institute (AISI).
Fellows will receive comprehensive financial support that covers their living expenses and research costs, along with dedicated resources for building foundational knowledge in AI safety, regular mentorship, 1:1 coaching calls with our team, and facilitation for in-person work with the partner organisations.
Who is eligible?
Candidates who would be available for full-time work for at least 3 months starting February or March 2025.
Candidates around the globe, including those from regions traditionally underrepresented in AI safety research.
Applicants who will be under 18 years of age in January 2025 can not be accepted as of now
How do placements work?
After completing the selection phase, candidates will receive full-time placement offers from partner organisations
Fellows will work as colleagues with researchers from the respective organisations, though the name and scope of their roles may vary.
Although the start date of the fellowship will be mutually decided by the candidate and the placement org, Fellows are expected to begin applying for visas from February 2025 onwards.
Fellows who perform well would have reliable opportunities to continue working full-time with the placement orgs.
Ideal candidates should have:
Demonstrated knowledge of Machine Learning and Deep Learning (e.g. a first-author ML research paper).
Demonstrated programming experience (e.g. >1 year of software engineering experience at a leading tech firm).
Scholastic excellence or any other achievements, such as 99th percentile performance in standardised STEM tests, like Math or Informatics Olympiads or competitive exams for graduate study.
An interest in pursuing research to reduce the risks from advanced AI systems.
Even if you feel you don’t possess some of these qualifications, you are encouraged you to apply!
