We're looking for a computational biologist to serve as the bridge between our AI systems and physical reality. We need someone who can programmatically QA the high-volume outputs of our AI before they reach the bench - catching errors that are invisible to humans but obvious in the data.
• Validate AI outputs using computational methods - simulations, structural analysis, database cross-referencing
• Translate AI predictions into executable protocols for cloud labs (Emerald, Strateos) or technical specs for CROs
• Build and maintain validation pipelines that catch errors before they waste lab resources
• Manage the "hand-off" between digital predictions and physical experiments
• Transform JSON outputs from our agents into experimental protocols and validation workflows
• PhD in Computational Biology, Bioinformatics, or related field preferred - or equivalent exceptional experience
• Strong proficiency in Python and/or R for data analysis and pipeline development
• Experience with computational validation methods (molecular simulations, structural analysis, sequence analysis)
• Ability to critically evaluate biological predictions and identify potential issues
• Comfort working at the interface of software and biology
• Experience with cloud lab platforms (Emerald, Strateos, or similar)
• Background working with CROs or translating computational work to wet-lab execution
• Familiarity with AI/ML systems and their failure modes
• Experience red-teaming or adversarially testing scientific predictions
• Work at the cutting edge of AI-driven biology
• Fully remote - work from anywhere
• Small team where your expertise directly shapes our science
• Competitive compensation with token/equity component
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