Anthropic Fellows Program

About the role

The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure to work on an empirical project aligned with our research priorities, with the goal of producing a public output.

Responsibilities

• Work on an empirical project aligned with Anthropic's research priorities.
• Receive direct mentorship from Anthropic researchers.
• Access to a shared workspace (in either Berkeley, California or London, UK).
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits.
• Funding for compute (~$15k/month) and other research expenses.

Requirements

• Fluent in Python programming.
• Available to work full-time on the Fellows program.

Qualifications

• Motivated by making sure AI is safe and beneficial for society as a whole.
• Excited to transition into empirical AI research and would be interested in a full-time role at Anthropic.
• A strong technical background in computer science, mathematics, or physics.
• Thrives in fast-paced, collaborative environments.
• Can implement ideas quickly and communicate clearly.

Skills

• Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity).
• Experience in areas of research or engineering related to their workstream.

Benefits

• Full-time research opportunity.
• Direct mentorship from Anthropic researchers.
• Access to a shared workspace (in either Berkeley, California or London, UK).
• Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits.
• Funding for compute (~$15k/month) and other research expenses.

Pay

The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).

Schedule

Full-time research opportunity.

Anthropic Institute Fellows (Economics & Policy)

• Designing and conducting empirical research on AI's economic effects, drawing on external data sources.
• Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society.
• Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale.
• Making sure model performance increases with custom harnesses?
• Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems?
• Identifying which metrics relating to AI R&D could serve as early warning signals for recursive self-improvement.