Research Advisor - Computational Genomics

Lilly • San Diego, CA

1d

About The Position

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
We are seeking a highly motivated computational genomics scientist to join our team and contribute to high-visibility research on RNA therapeutics. The Lilly Genetic Medicine (LGM) team is an innovation-focused group working to identify, develop, and apply cutting-edge technologies to deliver maximum benefit to our patients. Our Data Science and AI/ML team collaborates with experimental scientists from diverse backgrounds, contributing to study design, scalable genomics infrastructure, and data-driven discovery that accelerates the RNA therapeutic pipeline.

Requirements

• PhD degree in bioinformatics, computational biology, computational genomics, integrated biomedical sciences, or a related field
• Demonstrated expertise with standard bioinformatics tools, pipelines, and databases for genomic analysis
• Strong programming skills in Python, R, or similar languages
• Experience with high-throughput, high-dimensional NGS data analysis and interpretation
• Excellent written and oral communication skills with ability to present complex data to diverse audiences
• Demonstrated ability to work collaboratively in cross-functional team environments
• Self-directed and highly motivated individual with strong learning agility

Nice To Haves

• Extensive experience developing scientific solutions using Python, R, or similar languages
• Experience working with High-Performance Computing and/or cloud environments
• Experience with workflow orchestration platforms such as Seqera Platform (Nextflow Tower) and community-maintained pipelines (e.g., nf-core/rnaseq) for scalable, reproducible analysis
• Hands-on experience with RNA-seq analysis tools for alignment, gene expression quantification and pathway analyses
• Hands-on experience with spatial transcriptomics (e.g., Visium, Xenium) and single-cell RNA-seq analysis (e.g., Seurat, Scanpy)
• Exposure to AI/ML methods applied to biological sequence data or drug discovery (e.g., regression, deep learning, generative models for sequences)
• Deep understanding of nucleic acid, cellular, and molecular biology; familiarity with RNA therapeutics biology is a strong plus
• Demonstrated knowledge of genetics and molecular biology, particularly as they relate to RNA
• Track record of peer-reviewed publications in bioinformatics, computational biology, or a closely related field
• Experience in algorithm development, statistics, data management, data mining, data visualization, and/or analytics

Responsibilities

• Build and maintain production NGS analysis pipelines scaled for high-throughput RNA drug discovery including bulk RNA-seq, smRNA-seq, SHAPE-seq, and eCLIP-seq assays
• Own the full data path from sequencer output through QC to DataLake ingestion, ensuring data integrity, reproducibility, and accessibility for downstream analysis and ML ready data
• Design and execute analytical strategies for spatial transcriptomics and single-cell sequencing to resolve cellular heterogeneity and tissue-level biology relevant to RNA therapeutics
• Support and contribute to ML model development connecting RNA sequence design and chemistry to pharmacology outcomes, including potency and off-target liability prediction
• Partner with enterprise AI, Statistics, and Tech@Lilly teams to translate platform-level AI/ML capabilities into RNA-specific tooling and reusable analytical assets
• Contribute to reusable data assets and standardized analysis frameworks that support downstream machine learning and cross-program integration
• Generate visualizations and reports to communicate results to stakeholders; participate in scientific discussions and present findings to the team

Benefits

• company bonus (depending, in part, on company and individual performance)
• company-sponsored 401(k)
• pension
• vacation benefits
• medical, dental, vision and prescription drug benefits
• flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
• life insurance and death benefits
• certain time off and leave of absence benefits
• well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees