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BigHat Biosciences is seeking a Scientist I to join the Display Technologies team, contributing to antibody discovery and engineering efforts. You will generate high-quality experimental data to improve BigHat's machine learning models, working closely with senior scientists and cross-functional teams including Data Science and ML.
Key responsibilities include:
- Support R&D projects advancing display technologies that expand antibody discovery capabilities and feed ML models
- Lead construction and quality control of phage display libraries across diverse antibody formats (VHH, scFv, Fab) using molecular biology techniques such as PCR, molecular cloning, and electroporation
- Execute standard phage display selections to engineer antibodies with desired therapeutic properties
- Express, purify, and characterize display-derived molecules using assays including ELISA, flow cytometry, BLI/SPR, and CE-SDS
- Analyze selection results and contribute to discussions on experimental design and next steps
- Collaborate with Data Science and ML teams to inform library design and interpret selection data for model training
- Work closely with leadership and cross-functional teams to ensure alignment between strategy, research, and development
- Present experimental plans and results during regular team meetings
- Communicate results effectively to decision makers, the broader team, and external partners
- Maintain thorough records using LIMS and electronic notebooks
Requirements:
- Ph.D. in Biochemistry, Structural Biology, Protein Engineering, or related field with up to 2 years of industry research experience; OR M.S. in a related field with 6+ years of relevant industry research experience
- Experience with display technologies, including library design and selection strategies
- Knowledge of antibody biology and protein expression
- Strength in general molecular biology techniques (PCR, molecular cloning, gel electrophoresis)
- Demonstrated ability to follow protocols carefully, troubleshoot experiments, and maintain detailed lab records
- Effective time management and clear written and verbal communication skills
- Collaborative, team-oriented mindset with eagerness to learn in a fast-paced startup environment
- Scientific track record and publication record
- Strong data analysis and interpretation skills
Nice-to-haves:
- Experience with flow cytometry, ELISA, or other binding assays
- Familiarity with NGS or automation platforms
- Experience working with agentic software tools
