Computational Biologist

Job description

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