Postdoctoral Researcher - Genomics, Proteomics, and Clinical Outcomes

Eli Lilly and • Boston, MA

105d • $58,000 - $100,320

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. The Diabetes, Obesity and Complications Therapeutic Area (DOCTA) of Eli Lilly and Company, focuses on the discovery of biologic, small molecule and genetic therapeutics for the treatment of diabetes, obesity and associated complications. The successful candidate will be responsible for supporting the data, tools and infrastructure that are critical for enabling research and development objectives that will inform and accelerate the discovery and development of our next generation therapeutics. Specifically, we are seeking a key multi-dimensional individual to integrate and analyze genomic, proteomic, metabolomic and phenotypic data from publicly available biobank and proprietary data sets on cloud based clinical multi-omics platforms. We are seeking a Statistical Geneticist with expertise in whole genome sequencing (WGS), proteomics, and clinical outcomes analysis to advance our research in identifying novel therapeutic targets. This role will involve analyzing large-scale biobank and population-cohort datasets to uncover genetic and molecular factors associated with disease risk, progression, and treatment response. You will operate as part of the DOCTA Data Science and Computational Biology (DSCB) team and partner with early discovery scientists and clinicians, translational scientists, bioinformaticians and geneticists. This is an exciting opportunity to advance precision medicine and therapeutic target identification through innovative statistical genetics approaches. If you are passionate about using big data for scientific discovery and therapeutic application, we encourage you to apply!

Requirements

• PhD in statistical genetics, bioinformatics, computational biology, biostatistics, or a related quantitative field

Nice To Haves

• Expertise in whole genome and whole exome sequencing analysis, proteomics, metabolomics and other molecular data analysis, and clinical outcomes research.
• Strong proficiency in statistical modeling, machine learning, and high-dimensional data analysis.
• Experience working with large biobank and cohort datasets (e.g., UK Biobank, All of Us, FinnGen).
• Proficiency in programming languages such as R, Python, and SQL for data analysis.
• Familiarity with genetic association studies, GWAS, and polygenic risk scores.
• Excellent communication and collaboration skills to work effectively in cross-functional teams.
• Experience in pharmaceutical or biotech industry settings.
• Knowledge of functional genomics and multi-omics data integration.
• Strong publication record demonstrating contributions to statistical genetics and biomarker discovery and analysis.
• Prior experience in cardiometabolic research.
• Prior experience with polygenic risk score models.

Responsibilities

• Apply statistical and computational approaches to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery.
• Conduct rigorous analyses of large-scale population cohorts and biobank datasets to identify genetic variants and causal genes associated with disease outcomes.
• Develop and implement machine learning and bioinformatics pipelines to integrate multi-omics data.
• Collaborate with interdisciplinary teams, including geneticists, epidemiologists, and clinicians, to interpret findings and guide therapeutic development.
• Prepare scientific reports, presentations, and publications detailing research outcomes.
• Contribute to the development of novel statistical methods for analyzing high-dimensional biological data.

Benefits

• Eligibility to participate in a company-sponsored 401(k)
• Pension
• Vacation benefits
• Eligibility for 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
• Industry: Chemical Manufacturing
• Education Level: Ph.D. or professional degree