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Eli Lilly and Company Postdoctoral Fellow - R-8886 in Indianapolis, Indiana

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 39,000 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. Were looking for people who are determined to make life better for people around the world.Company Overview:At Lilly, we serve an extraordinary purpose. For more than 140 years, we have worked tirelessly to discover medicines that make life better. These discoveries start in Lilly Research Laboratories, where our scientists work to create new medicines that will help solve our worlds greatest health challenges. We explore how next generation therapeutics, new technologies, and data analytics can improve patient health and the healthcare system. We share a real passion for challenging conventional wisdom and creating an environment that embraces creative, break-through concepts.Responsibilities:Machine learning (ML) shows promising opportunity for finding novel targets and biomarkers by mining large datasets. Natural language processing, feature preprocessing, and feature engineering are challenging when working with high-dimensional data, which may have 100s of thousands of genomic, chemical, or clinical features and mapping them successfully to biological context such as pathways and networks. As a post-doctoral fellow, you will have the opportunity to develop algorithms and methods to work with large biological datasets, work on novel therapeutics. The team uses quantitative approaches to leverage large, disparate data types to better understand underlying biology of disease and model how patients could respond to treatments. We are seeking a highly motivated scientist to join a team that can independently conceive of and execute experiments based on discussions with scientific partners.Key objectives and deliverables:Develop investigational hypotheses, generate, and optimize experimental designs to characterize novel targets.Assess and help select new technologies and external vendors to drive cost efficient and informative assays to answer key scientific questions.Lead strategic collaborations with academic and industrial collaborators.Mentor team members to develop analytical skills and enhance an environment conducive to learning and sharing information.Continued academic leadership by oral and poster presentations at key conferences.Authorship of publications in peer-reviewed journals.Basic Qualifications:PhD in statistical genetics, bioinformatics, mathematics, statistics, computer or biological disciplinesPrior hands-on experience in one or more of the following areas: bioinformatics, statistics, machine learning, artificial intelligenceAdditional Skills/Preferences:Demonstrable experience with feature engineering techniques in publications and/or open-source contributions (e.g: GitHub)Proficiency with one or more general scripting languages such as Python, Perl, or Ruby, and data visualization tools (Spotfire, R, Python).Comfortable with Unix/Linux, SGE clusters, shell scripting.Experience in high-performance storage and compute environment using Amazon Web Services (AWS), Sun Grid Engine, Hadoop ecosystem such as HDFS and SparkKnowledge and hands-on experience of major public and commercial information databasesWorking experience with real world healthcare data, pharmaceutical industry research information, and/or clinical research data (biomarkers, NGS, omics data) preferred.Experience in ChemInformatics, especially de novo synthesis, docking, or protein folding predictions.Experience with structural biology, such as CryoEM and Xray crystallography.Experience handling data-driven research from project inception to result communication.Proven strong authorship

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