Lead bench-based developability assessments for late-stage AI-designed biologic drug candidates. Design and execute dose-solution compatibility and stability studies, develop chromatography-based protein characterization methods, support formulation and stress testing, interpret biophysical and analytical data, manage CRO testing, and communicate findings and recommendations across the organization.
The role: BigHat Biosciences is looking for a hands-on, bench-driven scientist to perform IND-enabling developability assessments on late stage drug candidates from our Milliner Platform for AI-designed therapeutics. This is a lab-based 12-month contract role, with the possibility but no guarantee of conversion to full-time position. You'll spend the majority of your time at the bench executing complex stability studies.
Key Responsibilities
- Lead, design, and execute in-use dose solution studies to assess drug compatibility with administration materials.
- Develop highly sensitive protein characterization methods (qSEC, RP-HPLC, CEX, particle counting, etc) for assessing drug quality and recovery.
- Support late-stage characterization, including formulation screening, stress testing, and peptide mapping, to rank and advance lead candidates.
- Drive developability assessments (purity, stability, tolerability, biophysical properties) across programs, with strong attention to data interpretation and organization.
- Communicate with and manage external CROs for testing and analytics.
- Interpret and communicate scientific findings, propose next steps, and broadcast clearly across the organization.
- Proactively identify and scope state-of-the-art analytical tools and developability technologies.
Skills Knowledge and Expertise
- PhD in Biochemistry or relevant discipline with 5+ year(s) of industry experience; exceptional non-PhD candidates with deep bench experience will be considered.
- Experience developing and optimizing sensitive analytical chromatography-based methods is a must.
- Strong background in biophysical and analytical characterization of antibodies and antibody fragments: SEC, HIC, CE-SDS, DLS, DSF, ELISA, LC-MS.
- Track record of translating complex data into clear results and recommended actions.
- Enthusiastic about learning and onboarding new technologies to expand capabilities and improve work quality, timelines, throughput or cost.
About
BigHat Biosciences designs safer, more effective biologic therapies for patients using machine learning and synthetic biology. BigHat integrates a wet lab for high-speed characterization with machine learning technologies to guide the search for better antibodies. We apply these design capabilities to develop new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases.BigHat is a Series B biotech outside San Francisco with a team-oriented, inclusive, and family-friendly culture. Our broad pipeline of wholly-owned and partnered therapeutic programs span many disparate indications with high unmet need, such as cancer, inflammation, and infectious disease. BigHat has raised >$100M from top investors, including Section 32, a16z, and 8VC.
BigHat Biosciences San Mateo, California, USA Office
1900 Alameda de Las Pulgas, San Mateo, CA, United States, 94403
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