Our mission is to generate new therapeutic opportunities by advancing AI and experimental technologies for drug design. Using AI and massively parallel experimentation, we design antibodies that precisely bind the disease target at the right location, while minimizing manufacturability and toxicity risks. We are a well-funded, revenue-generating, bilingual company of wet- and dry-lab scientists, and are founded by AI and protein design experts from Harvard University.
The role
Fueled by partnerships and increasing demand for internal R&D, we will be looking to you to help scale our antibody engineering and developability measurement pipeline and apply it toward solving hard antibody design problems. This will include:
Designing and performing high-efficiency DNA library cloning and construction
Executing yeast display selections coupled to MACS/FACS and NGS to characterize libraries of protein and antibody variants
Optimizing therapeutic candidates in lead programs to have desired affinity and developability properties
Working together with our dry-lab and other wet-lab scientists to establish a rapid and seamless production and testing pipeline for characterizing machine learning generated antibody designs
Qualifications
You have a Ph.D. or equivalent accomplishments in molecular or cell biology, biochemistry, or a related field
You have a track record of designing, implementing, and optimizing library-style cloning and screening campaigns using display (especially yeast surface display)
You have expertise in some or all of the following: MACS/FACS, NGS, BLI, SPR, ELISA, and associated data analysis
Well-organized, and would enjoy establishing an operationally efficient antibody characterization pipeline that works reliably
Interested in working in a high-intensity, fast-paced environment often driven by deadlines
Problem-focused, and value unblocking colleagues before yourself, and are excited to mentor/train junior colleagues
Send a CV and why you're interested in working with us to hiring@nabla.bio.