Computational Biologist
Bio ProtocolAbout the role
Bio is a decentralized science protocol that helps launch and grow AI-driven biotech research. It enables scientists to raise funds, create value from their work, and distribute that value directly to their communities. Since 2023, Bio has directed over $50m to global researchers, offering an alternative to traditional pharma funding. Backed by investors like Binance Labs, Northpond Ventures, and Animoca Brands, Bio accelerates real-world therapeutics across longevity, brain health, fertility, psychedelic science, and more.
The Role
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.
What You'll Do
- 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
What We're Looking For
- 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
Nice to Have
- 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
Why Bio
- 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
Skills & tech stack
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