Jun Li

Jun Li

Senior Principal Scientist, Late Stage Translational Bioinformatics Oncology @ Bristol Myers Squibb

About Jun Li

Jun Li is a Senior Principal Scientist in Late Stage Translational Bioinformatics Oncology at Bristol-Myers Squibb, specializing in biomarker discovery and development with extensive experience in bioinformatics and computational biology.

Current Position at Bristol-Myers Squibb

Jun Li is the Senior Principal Scientist in Late Stage Translational Bioinformatics Oncology at Bristol-Myers Squibb in New Jersey. In this role, Jun Li leads the Translational Bioinformatics efforts for bladder and prostate oncology biomarker programs. He also provides genomics and bioinformatics support to multiple therapeutic areas.

Previous Experience at Merck

Jun Li worked as a Senior Research Scientist in Research Solutions & Bioinformatics at Merck from 2009 to 2013. During his four years at the company based in Rahway/Kenilworth, New Jersey, he contributed to bioinformatics research projects and solutions.

Role at GlaxoSmithKline

Jun Li held multiple positions at GlaxoSmithKline, including Principal Scientist and Computational Biologist in Bioinformatics from 2001 to 2009 and as an Information Technologist from 2001 to 2002. His work locations included Research Triangle Park, North Carolina, and King of Prussia, Pennsylvania. His roles involved supporting bioinformatics and computational biology efforts across various therapeutic areas.

Educational Background

Jun Li holds a PhD in Biochemistry from McGill University and an MSc in Computer Science from Villanova University. He completed his postdoctoral studies in Biochemistry/Biophysics at the University of Pennsylvania School of Medicine and is a Certified Project Manager from the Project Management Leadership Group.

Expertise in Translational Bioinformatics

Jun Li specializes in bioinformatics, data integration, pathway/network analysis, text/data mining, biomarker identification, target ID and validation, gene expression analysis, sequencing analysis, molecular biology, biochemistry, statistics, computer programming, systems biology, project management, RNA therapeutics, and drug discovery and development. He has extensive experience constructing research strategies for biomarker discovery and translating information from basic research to clinical applications.

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