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Call for Applications: SPAR – Research Program for AI Risks (Fall 2026 Cohort)

Application Deadline: August 18, 2026

About the Program

SPAR is a part-time, remote research fellowship designed to enable aspiring AI safety and policy researchers to gain practical research experience while working on impactful projects alongside experienced professionals in the field. The programme pairs aspiring researchers with professionals who are actively addressing risks associated with artificial intelligence. Through this collaboration, mentees receive valuable research experience, mentorship and guidance, while mentors benefit from working with capable and motivated research collaborators. The fellowship offers a flexible time commitment of approximately 5–40 hours per week, allowing participants to fit their research activities around other academic, professional or personal commitments. The programme runs for three months and involves structured research conducted entirely remotely. Eligibility is open to mentees with relevant technical or policy backgrounds at different career stages, ranging from undergraduate students to mid-career professionals. The programme culminates in a Demo Day featuring research posters, presentations and a career fair, providing participants with opportunities to showcase their work and connect with organisations such as METR, Redwood Research, GovAI and MATS.

Research Areas

SPAR supports a broad range of research that is helpful for helping society mitigate the risks posed by advanced AI, including:

AI Safety: Ensuring powerful AI systems follow human intentions
AI Policy: Governing the development of transformative AI
AI Security: Hardware-enabled governance and preventing the theft of model weights
Interpretability: Reverse-engineering neural networks and their internal representations
Biosecurity: Preventing or preparing for AI-enabled bioattacks
Societal Impacts: Understanding the effect of transformative AI on society and the economy

Why Apply

Research Experience: Build the skills to break into technical AI safety, AI policy, or biosecurity research and learn whether this path is right for you
Expert Mentorship: Get advice and support from experienced researchers to support your development of key scientific skills
Career Opportunities: Most projects in SPAR result in papers. Demo Day gives you the opportunity to present your research in front of researchers from organisations like METR, Redwood Research, GovAI, and MATS
Community: Join a research team of peers with shared interests who support each other’s growth. Virtual coffee chats and in-person meetups provide additional opportunities to connect
Impact: Conduct real, cutting-edge research to help the world answer the most pressing questions of our time. Most projects lead to published papers or preprints with mentee co-authors
Prizes: Last year, $7,000 total was awarded at Demo Day, which rewards the best posters and talks for projects in the program

What to Expect

Step 1: Browse Projects: Explore available projects and apply to work on ones you’re excited about.

Step 2: Conduct Research: Spend 5-40 hours per week on real catastrophic risk research with your team. Receive structured support and regular feedback.

Step 3: Present at Demo Day: Present your research at the virtual mini-conference attended by leading AI safety organisations. The best posters and lightning talks will be eligible for prizes.

Step 4: Continue & Collaborate: Many mentorship pairs continue working together after the program ends, leading to publications and career opportunities.

Eligibility

The program is open to undergraduate, graduate/PhD students, and professionals of different experience levels. Mentors often look for a technical background (e.g., ML, CS, cybersecurity, math, biology, physics, etc.) or knowledge relevant to policy and governance (e.g., law, international relations, public policy, political science, economics, etc.). Some projects may require additional background knowledge, like knowledge of specific research areas, techniques, or tools (e.g., ML frameworks). Previous research experience is not required, and many mentees have none. Even if you do not entirely meet these criteria, you are encouraged to apply. Many past mentees have been accepted even though they didn’t completely match a project’s criteria.

Timeline (Fall 2026)