Computational Biologist – Obesity Research

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 new therapeutic approaches for the treatment of diabetes, obesity and cardiometabolic diseases. Starting from an idea, we work with partners across Lilly to discover and develop novel biologic, small molecule and nucleic acid-based therapeutics. Our focus is the patient: by understanding the biology and pathophysiology underlying disease states, we aim to address the root cause of disease, and develop breakthrough therapies. We have one of the strongest pipelines in the industry and a track record of delivering impactful medicines that improve people’s lives.

Are you a computational scientist passionate about addressing some of the most pressing global health challenges of our time? Do you stay current with the latest advances in metabolic disease research and obesity pathophysiology? Are you eager to apply pioneering computational and statistical approaches to analyze multi-omics data and unravel the complex biology of obesity, adipose tissue function and metabolic dysregulation?

The computational biology role within DOCTA is an exciting opportunity for a team-oriented scientist with deep expertise in obesity biology and computation methods to drive therapeutic discovery in metabolic diseases. In this hands-on role, you will work cross-functionally with researchers across DOCTA to design and implement multi-omic studies specifically focused on obesity pathophysiology, energy regulation, adipose tissue biology, metabolic pathway dysregulation and CNS pathways concerning obesity. You will collaborate closely with experimental project leads and scientific domain experts to drive scientific discovery through the comprehensive analysis of single-cell genomics data from preclinical models and human studies. In this role, you will not only apply established computational methods to understand obesity pathophysiology and identify novel therapeutic targets in metabolic pathways, but also pioneer the application of innovative AI/ML approaches to extract deeper biological insights from complex multi-modal datasets. The successful candidate will have the opportunity to directly impact the DOCTA pipeline, ultimately driving the scientific field forward and bringing innovative therapies to patients.

Key Responsibilities:

• Design and complete studies using omics-related data sources, including RNA-seq, spatial transcriptomics, single-cell omics, proteomics, functional genomics, metabolomics, and more.  
• Integrate standard analytical approaches as well as emerging AI/ML models to answer scientific questions of high-dimensional data
• Partner with discovery statistics team to create novel analytical frameworks for high-throughput studies and develop specialized methodologies to enhance insights from small-sample datasets.
• Stay up-to-date on current technical and scientific advances through deep understanding of the literature and attendance of relevant technical and disease-related conferences
• Clearly communicate complex results to cross-functional partners in a prompt and transparent manner
• Perform ad-hoc bioinformatics analyses and data visualizations as needed
• Work collaboratively with other Data Sciences and Computational Biology (DSCB) scientists to develop innovative, best in class computational workflows and data repositories for advanced analyses
• Engage in code and documentation review within the team and across other teams within the DSCB team
• Adhere to industry-standard protocols for scientific project documentation

Basic Requirements: 

PhD or equivalent in Computational Biology, Bioinformatics, Biomedical Informatics, or related field with 2+ years of experience post-PhD in relevant disease area.

Additional Skills/Preferences:

• Strong track record of execution of computational biology and/or bioinformatics-based projects, potentially including RNA-seq, metabolomics, multi-omics, human genetics, proteomics, AI/ML, and other related research modalities required
• Prior experience and deep expertise in obesity and related areas, preferably with data from preclinical models, patient cohorts or cell lines preferred    
• Expertise in programming languages including R and Py