Thomas Sheffield
About Thomas Sheffield
Thomas Sheffield is a Postdoctoral Researcher at Sandia National Laboratories with a background in computational and applied mathematics, physics, and biology. He has previously worked at various institutions including UT Southwestern Medical Center, the EPA, and Southern Methodist University.
Current Position at Sandia National Laboratories
Thomas Sheffield currently works as a Postdoctoral Researcher at Sandia National Laboratories in Livermore, California. Beginning in 2022, Sheffield's role encompasses a variety of research projects aimed at addressing complex scientific challenges. His work at this national laboratory synthesizes his extensive experience and aligns with his academic and professional background in applied sciences.
Previous Experience at UT Southwestern Medical Center
From 2020 to 2021, Thomas Sheffield served as a Postdoctoral Researcher at UT Southwestern Medical Center in the Dallas/Fort Worth Area. During his tenure, he engaged in biomedical research, contributing to advanced studies and collaborative efforts within a leading medical institution. This engagement further reinforced his career shift towards biological and medical research.
Role at US Environmental Protection Agency
Thomas Sheffield worked with the US Environmental Protection Agency as an ORISE Postdoctoral Researcher from 2017 to 2019 in the Raleigh-Durham, North Carolina Area. Here, he conducted research focused on environmental sciences, which provided him the opportunity to address ecological and public health issues through scientific investigation.
Academic Background
Thomas Sheffield holds a PhD and a Master of Science in Computational and Applied Mathematics from Southern Methodist University, where he studied from 2012 to 2017. He also earned a Bachelor of Science in Physics and a Bachelor of Arts in Mathematics from Texas Christian University, completed between 2005 and 2009. His strong academic foundation has been influential in his multidisciplinary research endeavors.
Research on COVID-19 Variants
Thomas Sheffield developed a keras-based model to predict human ACE2 binding, expression, and antibody escape for COVID-19 variants using spike sequence mutations. He collaborated with experimentalists to develop and analyze in-house experiments to validate and improve predictive models. This research was presented at the CBDST 2022 conference, showcasing the potential impact of his work on understanding viral variant pandemic potential.