Machine Learning Scientist/Sr Scientist - Antibody Property Prediction & Generative Design at Eli Lilly and Company

Indianapolis, Indiana, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Biotechnology, Pharmaceuticals, HealthcareIndustries

Requirements

PhD in Computational Biology, Protein Engineering, Immunology, Biochemistry, or related field from an accredited college or university
Minimum of 2 years of experience in antibody or protein therapeutic development within the biopharmaceutical industry
Strong experience with protein sequence analysis and structural biology
Proven track record in machine learning applications to biological sequences
Deep understanding of antibody structure-function relationships and immunology

Responsibilities

Antibody Property Prediction: Build multi-task learning frameworks specifically for antibody properties including binding affinity, specificity, stability (thermal, pH, aggregation), immunogenicity, and developability metrics from sequence and structural features
Antibody Sequence Generation: Develop and implement generative models (transformers, diffusion models, evolutionary models) for antibody design, including CDR optimization, humanization, and affinity maturation while maintaining structural integrity
Structure-Aware Design: Integrate structural modeling and prediction (AlphaFold, ESMFold) with generative approaches to ensure generated antibodies maintain proper folding, CDR loop conformations, and epitope recognition
Developability Optimization: Create models that simultaneously optimize for multiple developability criteria including expression yield, solubility, viscosity, and post-translational modifications, crucial for manufacturing and formulation
Species Cross-Reactivity: Develop approaches to design antibodies with desired species cross-reactivity profiles for preclinical development, learning from cross-species binding data
Antibody-Antigen Modeling: Create models for predicting antibody-antigen interactions, epitope mapping, and paratope design, incorporating both sequence and structural information

Skills

Key technologies and capabilities for this role

Machine LearningDeep LearningSequence ModelingStructure PredictionMulti-task LearningAntibody EngineeringProtein DesignImmunologyBinding Affinity PredictionStability PredictionImmunogenicity PredictionDevelopability AssessmentFederated LearningAI Models

Questions & Answers

Common questions about this position

What is the employment type for this Machine Learning Scientist position?

The position is full time.

Is this Machine Learning Scientist role remote or office-based?

This information is not specified in the job description.

What key skills are required for the Antibody Property Prediction & Generative Design role?

The role requires deep expertise in antibody engineering, protein design, immunology, advanced machine learning for sequence modeling and structure prediction, generative models like transformers and diffusion models, and structural modeling with tools like AlphaFold and ESMFold.

What is the company culture like at Eli Lilly for this role?

Eli Lilly unites caring with discovery to make life better for people, puts people first, and emphasizes giving best effort to work while fostering collaboration through platforms like Lilly TuneLab that benefit both Lilly and biotech partners.

What makes a strong candidate for the Machine Learning Scientist/Sr Scientist position?

Strong candidates will have deep expertise in antibody engineering, protein design, immunology, and advanced ML techniques for antibody property prediction, generative design, and structure-aware modeling.

Eli Lilly and Company

Develops and delivers prescription medicines globally

About Eli Lilly and Company

Eli Lilly and Company is a global pharmaceutical company that focuses on discovering, developing, and delivering medicines to improve health. The company has a long history of scientific achievements, including the creation of insulin, the first life-saving treatment for diabetes. Lilly's operations involve extensive research and development to create new medications and enhance existing ones, ensuring they are safe and effective. Their products are primarily prescription medicines sold to healthcare providers for various medical conditions, including diabetes, cancer, and pain management. What sets Lilly apart from its competitors is its strong commitment to ethical practices and the protection of its products from counterfeiting. The company's goal is to enhance lives through innovative medical solutions while maintaining high standards of quality and ethics.

Indianapolis, IndianaHeadquarters

1876Year Founded

$1,180.1MTotal Funding

IPOCompany Stage

Biotechnology, HealthcareIndustries

10,001+Employees

Risks

Competition from Novo Nordisk's Ozempic may impact tirzepatide's market share.

Potential construction delays in Indiana could affect GLP-1 drug production timelines.

Regulatory challenges may hinder Kisunla's expansion in new Alzheimer's markets.

Differentiation

Eli Lilly's rich history includes the first life-saving insulin treatment.

Lilly's strategic partnerships enhance its position in neurodegenerative disease treatments.

FDA approval of Zepbound opens new therapeutic markets for sleep disorder treatments.

Upsides

Lilly's $9 billion complex in Indiana boosts GLP-1 drug production capacity.

Kisunla's approval in China expands Lilly's Alzheimer's treatment market in Asia.

Collaboration with EVA Pharma enhances Lilly's reputation as socially responsible.

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