Advisor - Computational Biology

Role Summary

Advisor - Computational Biology at Lilly Gene Therapy. Join a cross-functional team focused on inventing, characterizing, and advancing genome therapy reagents to deliver on the promise of gene therapy to patients around the world.

Responsibilities

• Design, execute, and maintain bioinformatics pipelines for analyzing bulk and single-cell RNA sequencing, AAV integration analysis, vector genome sequencing, and capsid library screening data.
• Perform end-to-end NGS data analysis including quality control, variant calling, differential expression analysis, and biological interpretation
• Develop computational methods for AAV vector characterization, including integration site analysis, biodistribution assessment, and tissue-specific biological interpretation
• Support AAV capsid engineering through computational analysis of structure-function relationships and receptor binding prediction
• Analyze transcriptomic and proteomic datasets to identify therapeutic targets and biomarkers for gene therapy
• Communicate and present experimental findings to internal teams and Lilly stakeholders
• Collaborate cross-functionally within Lilly Gene Therapy and Lilly Research Laboratories, ensuring milestones are met while adapting to evolving priorities

Qualifications

• PhD in Bioinformatics, Computational Biology, Genomics, or related fields
• Minimum 2 years industry experience in bioinformatics with focus on NGS data analysis and/or structural modeling
• Preferred: demonstrated publication record and familiarity with AAV biology, capsid engineering, and gene therapy applications

Skills

• Strong written and verbal communication, with ability to present complex data to diverse audiences
• Project management skills with ability to handle multiple concurrent projects
• Experience working in multidisciplinary teams and collaborative research environments
• Attention to detail and commitment to reproducible research practices
• Background in structural biology and protein engineering
• Experience with machine learning applications in biotechnology and drug discovery

Education

• PhD degree in Bioinformatics, Computational Biology, Genomics, or related scientific fields

Additional Requirements

• Travel up to 10-15% for conferences or training