Scientist, AI/ML — Antibody Developability

Role: Scientist specialized in AI/ML for antibody developability at Ginkgo Bioworks, focusing on building and benchmarking machine learning models to predict antibody biophysical properties. Responsibilities: develop validated predictive models using protein representations, implement rigorous evaluation frameworks for small datasets, assess cross-format transferability, perform QC on biophysical data, maintain automated pipelines, and communicate findings through scientific channels. Requirements: Ph.D. in Computational Biology, Bioinformatics, ML, Biophysics, or related field; strong proficiency in Python and scientific computing tools; experience with supervised ML on biological data; knowledge of protein representations like PLM embeddings; ability to analyze biophysical assay data. Preferred: familiarity with antibody formats (VHH, scFv), advanced supervised techniques, generative models, protein structure prediction, high-throughput experimental design, and software engineering fundamentals. HighValue: antibody developability, biophysical assays, AI/ML modeling, protein sequence and structure analysis, cross-format prediction (e.g., IgG to VHH-Fc), Boston-based hybrid work setup.