Why you should consider applying to a machine learning PhD

A PhD in Machine Learning and AI safety research represents a significant career path option for individuals interested in contributing to the development of safe artificial intelligence systems.

The core argument: Applying to PhD programs in Machine Learning should be seriously considered by junior AI safety researchers, particularly those who have completed programs like MATS or ARENA and are uncertain about their next career steps.

• Application deadlines are approaching quickly, with many programs closing on December 15th and some even earlier
• The application process is relatively low-cost in terms of time and resources, while potentially offering significant future value
• Candidates need not be completely certain about pursuing a PhD to benefit from applying

Key benefits of pursuing a PhD: A doctoral program provides a structured environment for developing crucial research capabilities and contributing to AI safety.

• PhDs offer stable funding, access to computing resources, and collaboration opportunities with established researchers
• The program provides intellectual freedom to pursue independent research ideas
• Academic credentials can open doors to positions in government agencies and larger organizations working on AI safety
• The path can lead to establishing AI safety labs as a professor at prestigious universities

Practical considerations: The PhD application process requires strategic planning and attention to detail.

• Strong letters of recommendation from established researchers are crucial
• Candidates should research potential advisors and programs thoroughly
• Application costs average around $80 per school
• The typical start date would be September 2025, providing time for additional career exploration

Important caveats: Not all candidates may find a PhD program to be the optimal path.

• Those who have determined technical AI safety research isn’t their strength may want to explore other contributions to the field
• Program quality matters significantly – experiences at lower-tier institutions may differ substantially
• The application process can take several days to weeks of dedicated effort
• ML PhD programs are highly competitive, requiring strong evidence of research competency

Future implications: The field of AI safety research continues to evolve rapidly, creating both opportunities and challenges for emerging researchers.

• The stability of independent research funding has become less predictable
• Academic institutions remain influential in shaping AI safety research
• PhD programs offer the flexibility to pivot to other opportunities if circumstances or priorities change

Strategic considerations: While pursuing a PhD represents a significant commitment, it maintains optionality while providing valuable research experience and credentials that could prove crucial in shaping the future of AI safety.