Scientist II, Display Technologies
$124,000–$155,000 year
On-siteSouth San Francisco, California, United States
Job Summary
Independently design, execute, and own phage display campaigns from library construction through panning and hit validation for soluble antigens and membrane proteins. Develop selection strategies, troubleshoot challenging targets, and optimize assays including flow cytometry, ELISA, and SPR. Build diverse display libraries using molecular biology fundamentals and partner with computational colleagues to generate and quality-control data at scale. Mentor associate scientists on experimental design and contribute to technical standards within the Display Technologies group. This Scientist II role focuses on end-to-end campaign ownership to feed AI antibody design models.
Required Qualifications
- PhD in Molecular Biology, Biochemistry, Immunology, Protein Engineering, or a related field
- 2–4 years of relevant industry experience
- Significant hands-on expertise with antibody/protein discovery by phage display, including library design, build, panning/selection, and hit validation
- Strong molecular biology skills for library construction, including cloning, mutagenesis, and assembly
- Hands-on flow cytometry (FACS) experience, including data interpretation and gating strategy
- Demonstrated ability to run campaigns independently and troubleshoot challenging targets
- Experience with membrane proteins (e.g., GPCRs) in cell-based expression systems or recombinant formats
- Strong working knowledge of antibody binding and characterization assays (e.g., ELISA)
- Proficiency in core molecular and cell biology techniques, including mammalian cell culture
- Excellent analytical and problem-solving skills
- Meticulous attention to detail
- Rigorous, organized approach to experimental design and documentation
- Strong written and verbal communication skills
- Ability to present complex scientific concepts to both technical and non-technical audiences
- Ability to work effectively in a collaborative, multidisciplinary team
- Track record of fostering knowledge-sharing and supporting more junior colleagues
Desired Qualifications
- Experience with label-free affinity characterization (SPR, BLI/Octet)
- Experience with alternative display formats (yeast, mammalian, or ribosome/mRNA display)
- Experience with lab automation (e.g., Hamilton, Tecan, or similar liquid handling)
- Working knowledge of scripting for analysis of large datasets (e.g., Python or R)
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