Advisor - Antibody Developability Validation & Benchmarking
Eli Lilly and Company
August 07, 2026
On-site
Boston, MA
Clinical Research and Development
Key Responsibilities:
- Build the canonical antibody developability benchmark suite (aggregation propensity, thermal stability, polyspecificity, self-interaction, viscosity, chemical liabilities, immunogenicity surrogates) and define joint/independent endpoint evaluation and multi-endpoint triage roll-up.
- Architect privacy-preserving, sequence-aware federated test set design with germline-, CDR-similarity-, and clonotype-based splits; account for antibody characterization asymmetry.
- Benchmark TuneLab federated antibody models against external resources (e.g., SAbDab, OAS, TAP, Jain et al. panel, FLAb).
- Develop cross-domain validation strategies across modalities/formats, expression systems, and assay protocols while respecting partner data boundaries.
- Implement temporal-split and sequence-similarity-aware validation to simulate prospective deployment, detect concept drift, and surface systematic failure modes.
- Partner on model design choices with validation implications (uncertainty quantification, calibration, structure-aware vs. sequence-only representations, endpoint combination).
- Ensure statistical rigor (multiple testing, hierarchical structure, non-independence) with honest confidence intervals; build reproducible MLOps pipelines.
- Perform performance profiling and integrate validation frameworks with TuneLab (NVIDIA FLARE) for scalable automated testing.
Basic Qualifications:
- PhD in Computational Biology/Bioinformatics/Computational Chemistry/Computer Science/Statistics (or related).
- 4+ years post-PhD in antibody discovery/engineering/developability data (biopharma or academic).
- Experience analyzing antibody developability assays (e.g., HIC, AC-SINS, nanoDSF, polyspecificity panels, viscosity, chemical liabilities).
- Hands-on antibody numbering (ANARCI or equivalent); working knowledge of Kabat/Chothia/IMGT numbering.
- Experience designing ML validation protocols for biological sequence data (similarity-aware splits, held-out test design).
Additional Preferences:
- Fine-tuning protein/antibody language models for property prediction (e.g., ESM-2, AbLang, IgBERT, AntiBERTa).
- Knowledge of sequence liability motifs; experimental design/statistical validation.
- Data engineering/automation; experience with NVIDIA FLARE (or Flower/OpenFL/PySyft).
- Antibody structure prediction tooling (AlphaFold-Multimer, IgFold, ABodyBuilder).
- Familiarity with public antibody resources (SAbDab, OAS, TAP, Jain panel, FLAb).
- Regulatory considerations for AI/ML in pharma; uncertainty quantification and calibration.
- PyTorch + ML ecosystem (Hugging Face, scikit-learn, RDKit); experiment tracking/model registry (MLflow, W&B).
- Publications; exceptional rigor; technical writing; balance validation with rapid partner value.
Role Location & Travel:
- Indianapolis, San Francisco, or Boston; up to 10% travel.
Compensation/Benefits:
- Anticipated wage: $166,500 - $266,200; eligibility for company bonus and comprehensive benefits (e.g., 401(k), healthcare, time off, life insurance, well-being benefits).
Application Instructions:
- If you require accommodation to submit a resume, complete the accommodation request form: https://careers.lilly.com/us/en/workplace-accommodation
- Build the canonical antibody developability benchmark suite (aggregation propensity, thermal stability, polyspecificity, self-interaction, viscosity, chemical liabilities, immunogenicity surrogates) and define joint/independent endpoint evaluation and multi-endpoint triage roll-up.
- Architect privacy-preserving, sequence-aware federated test set design with germline-, CDR-similarity-, and clonotype-based splits; account for antibody characterization asymmetry.
- Benchmark TuneLab federated antibody models against external resources (e.g., SAbDab, OAS, TAP, Jain et al. panel, FLAb).
- Develop cross-domain validation strategies across modalities/formats, expression systems, and assay protocols while respecting partner data boundaries.
- Implement temporal-split and sequence-similarity-aware validation to simulate prospective deployment, detect concept drift, and surface systematic failure modes.
- Partner on model design choices with validation implications (uncertainty quantification, calibration, structure-aware vs. sequence-only representations, endpoint combination).
- Ensure statistical rigor (multiple testing, hierarchical structure, non-independence) with honest confidence intervals; build reproducible MLOps pipelines.
- Perform performance profiling and integrate validation frameworks with TuneLab (NVIDIA FLARE) for scalable automated testing.
Basic Qualifications:
- PhD in Computational Biology/Bioinformatics/Computational Chemistry/Computer Science/Statistics (or related).
- 4+ years post-PhD in antibody discovery/engineering/developability data (biopharma or academic).
- Experience analyzing antibody developability assays (e.g., HIC, AC-SINS, nanoDSF, polyspecificity panels, viscosity, chemical liabilities).
- Hands-on antibody numbering (ANARCI or equivalent); working knowledge of Kabat/Chothia/IMGT numbering.
- Experience designing ML validation protocols for biological sequence data (similarity-aware splits, held-out test design).
Additional Preferences:
- Fine-tuning protein/antibody language models for property prediction (e.g., ESM-2, AbLang, IgBERT, AntiBERTa).
- Knowledge of sequence liability motifs; experimental design/statistical validation.
- Data engineering/automation; experience with NVIDIA FLARE (or Flower/OpenFL/PySyft).
- Antibody structure prediction tooling (AlphaFold-Multimer, IgFold, ABodyBuilder).
- Familiarity with public antibody resources (SAbDab, OAS, TAP, Jain panel, FLAb).
- Regulatory considerations for AI/ML in pharma; uncertainty quantification and calibration.
- PyTorch + ML ecosystem (Hugging Face, scikit-learn, RDKit); experiment tracking/model registry (MLflow, W&B).
- Publications; exceptional rigor; technical writing; balance validation with rapid partner value.
Role Location & Travel:
- Indianapolis, San Francisco, or Boston; up to 10% travel.
Compensation/Benefits:
- Anticipated wage: $166,500 - $266,200; eligibility for company bonus and comprehensive benefits (e.g., 401(k), healthcare, time off, life insurance, well-being benefits).
Application Instructions:
- If you require accommodation to submit a resume, complete the accommodation request form: https://careers.lilly.com/us/en/workplace-accommodation