Chemist

Highlights

• Evaluate frontier AI models for chemical safety risks in the CBRNE team.
• Test maximum agentic capabilities via synthesis planning and docking evaluations.
• Update harm frameworks to keep transformative AI safe for public benefit.

What they offer

• 15% bonus target
• equity
• benefits

Ideal candidate

A hands-on synthetic chemist with postdoc or industry experience who cares deeply about AI safety and preventing misuse of science while enabling legitimate research and communicating clearly to diverse audiences.

Requirements

• PhD in synthetic or computational chemistry or equivalent practical experience
• 2 years of post-doctoral, industry, or defense experience including wet-lab bench experience designing, executing, and troubleshooting multi-step syntheses
• Experience in cheminformatics and digital drug discovery tooling using Python (e.g., RDKit) to analyze reaction and bioactivity/toxicity datasets (e.g., QSAR) alongside ML or physics-based binding affinity prediction
• Experience with computer-aided synthesis planning (CASP), retrosynthesis tools, and 3D structure-based modeling such as molecular docking and pharmacophore modeling
• Experience working with Scientific AIs and applying LLMs to scientific problems