Datapoints, Ginkgo Bioworks' Bio × AI data generation platform, is seeking a Scientist to build and benchmark machine learning models that predict and design antibody developability. You will sit between our PROPHET-Ab high-throughput biophysical platform and the models it enables, working with both newly generated customer datasets and the GDPa public dataset series (clinical IgGs, sequence-diverse natural IgGs, bispecifics, VHH-Fcs), cross-format prediction, and generative design campaigns.

This computational role requires deep understanding of biophysical assay measurements, noise characteristics, and rigorous evaluation strategies for small-scale datasets. Ideal candidates are recent Ph.D. graduates with strong applied ML proficiency and interest in protein biophysics, motivated by integrated experimental and computational design.

Develop and validate predictive models for developability using PLM embeddings, structural features, and physicochemical descriptors.

Implement leakage-aware evaluation frameworks for rigorous performance assessment of small-scale datasets.

Evaluate cross-format transferability (IgG to VHH-Fc, bispecifics) and deploy data-efficient training strategies.

Perform rigorous QC on biophysical assay data to identify outliers and maintain high data integrity for modeling.

Maintain and develop automated pipelines to ensure reproducibility and facilitate technical reporting.

Disseminate findings through technical reviews, peer-reviewed manuscripts, and external scientific presentations.

Scientist, AI/ML — Antibody Developability

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Ginkgobioworks

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