Stephen Thomas
About Stephen Thomas
Current Position at Bristol Myers Squibb
Stephen Thomas is currently working at Bristol Myers Squibb as a Manager and Modeling Scientist in Summit, New Jersey, United States. His role includes applying advanced modeling techniques to solve complex scientific problems in the field of drug product development. He also holds the position of Modeling Engineer at the same company.
Previous Role at Celgene
Stephen Thomas previously worked at Celgene as a Modeling Engineer in Drug Product Development – Small Molecules in Summit, NJ, United States. His role likely involved leveraging his expertise in computational material modeling to advance small molecule drug development processes.
Educational Background
Stephen Thomas achieved a Doctor of Philosophy (Ph.D.) and a Master of Science (M.S.) in Materials Science and Engineering from Boise State University, where he studied from 2013 to 2018 and 2013 to 2017, respectively. Earlier, he obtained a Bachelor of Science (BS) in Computer Science from Periyar University from 2000 to 2004. He also completed his High School/Secondary Diplomas and Certificates from Toc - H public School from 1998 to 2000.
Previous Academic and Industry Experience
Stephen Thomas held a Postdoctoral Researcher position at the University of Tennessee for 10 months in Knoxville, Tennessee. Prior to this, he worked as a Graduate Assistant at Boise State University for 5 years. In the industry sector, he served as a Senior Systems Specialist at General Electric Company for 3 years in Bangalore, a Senior Software Engineer at Sasken for 2 years, and a Senior Software Engineer at Microview Technologies Pte Ltd for 4 years in Singapore.
Technical Expertise and Skills
Stephen Thomas has a strong background in coarse-grained molecular dynamics and software engineering. His expertise includes computational material modeling, reaction modeling in coarse-grained molecular dynamics (MD), finite element analysis, and thermal and elastic properties of materials. He has a keen interest in using the predictive capabilities of molecular scale modeling for industrial applications.