The Anthropic Fellows Program offers a unique opportunity for individuals interested in artificial intelligence research. This program aims to cultivate talent by providing funding, mentorship, and a platform for empirical projects. With a focus on reliable, interpretable, and steerable AI systems, Anthropic seeks to ensure AI is beneficial for society. The fellowship is designed for those passionate about AI safety and security, offering a chance to contribute to cutting-edge research.
About the Anthropic Fellows Program
The Anthropic Fellows Program is a four-month, full-time research initiative. It provides promising technical talent with the resources and guidance needed to conduct empirical projects aligned with Anthropic’s research priorities. The program emphasizes producing public outputs, such as paper submissions, with a history of fellows successfully publishing their work. Applications are reviewed on a rolling basis, with cohorts typically starting in September.
Program Structure and Benefits
Fellows can expect direct mentorship from Anthropic researchers and access to shared workspaces in Berkeley, California, or London, UK. The program also offers connections to the broader AI safety and security research community. Participants receive a weekly stipend of $3,850 USD, £2,310 GBP, or $4,300 CAD, along with country-specific benefits. Additionally, fellows are provided with substantial funding for compute resources, estimated at around $15,000 per month, and other research expenses.
Workstreams and Focus Areas
The program is expanding across various teams at Anthropic, offering several workstreams. These include AI Safety Fellows, AI Security Fellows, ML Systems & Performance Fellows, Reinforcement Learning Fellows, and Economics Fellows. While there’s overlap in skills and responsibilities, candidates can express preferences for specific workstreams. Each workstream has unique assessment steps and research areas.
AI Safety Fellows
This workstream focuses on developing techniques to ensure highly capable AI models remain helpful and honest, even as they surpass human intelligence. Research areas include scalable oversight, adversarial robustness, model organisms for misalignment, mechanistic interpretability, and AI welfare. Potential mentors include Sam Bowman, Sara Price, and Alex Tamkin. Past projects have explored topics like subliminal learning and open-source circuit tracing.
AI Security Fellows
The AI Security Fellows workstream aims to reduce catastrophic risks from advanced AI systems. Research areas involve creating methods to keep AI systems safe in unfamiliar or adversarial scenarios. Mentors for this track include Nicholas Carlini and Keri Warr. Past projects have demonstrated AI agents finding vulnerabilities in blockchain smart contracts and developing modular scaffolds for control evaluations.
ML Systems & Performance Fellows
This workstream concentrates on building and improving the systems that power AI research. Projects may involve developing CPU simulators, adding backends for different accelerators, or creating infrastructure for other research projects. Mentors like Alwin Peng and Zygi Straznickas guide fellows in this area. Strong candidates typically have robust software engineering skills and experience with large-scale distributed systems.
Reinforcement Learning Fellows
Fellows in this area work on projects related to understanding AI training data, improving its quality, and enhancing AI model capabilities through reinforcement learning. Research may involve building model-based tools, exploring generalization, or creating RL environments for safety-related tasks. Mentors include Ruhua Jiang and Kaidi Cao. This workstream requires strong software engineering skills and experience with ML systems.
Economics Fellows
The Economics and Policy workstream investigates the societal and economic impacts of AI. Projects involve designing and conducting empirical research on AI’s effects on labor markets and society, as well as analyzing the offense-defense balance for AI-enabled cyber and bio capabilities. Mentors include Maxim Massenkoff and Jack Clark. Candidates with an interest in economics or policy research are encouraged to apply.
Candidate Qualifications and Application Process
Candidates should be fluent in Python and available to work full-time for the program’s duration. A strong technical background in computer science, mathematics, or physics is beneficial. Anthropic encourages applications even if not every qualification is met, particularly from individuals in underrepresented groups who may experience imposter syndrome. The interview process includes an initial application and reference check, technical assessments, and interviews, culminating in a research discussion. Visa sponsorship is not provided for the fellowship program.
Frequently Asked Questions
What is the Anthropic Fellows Program?
It’s a four-month, full-time research program designed to help talented individuals conduct empirical projects in AI safety, security, and related fields, with funding and mentorship from Anthropic.
What are the benefits of participating in the program?
Fellows receive a weekly stipend, significant funding for compute resources, direct mentorship from Anthropic researchers, and opportunities to publish their research.
What are the different workstreams available?
The program includes workstreams for AI Safety, AI Security, ML Systems & Performance, Reinforcement Learning, and Economics, each with specific research areas.
What qualifications are needed to apply?
Applicants should be fluent in Python and have a strong technical background. While specific experience is beneficial, Anthropic encourages applications from those who may not meet every single requirement.
