Dr. Natalie LeMessurier is a computational chemist specializing in chemical physics, molecular dynamics, machine learning, and atmospheric chemistry. She earned her PhD from the University of Colorado Boulder, where her doctoral research focused on modeling gas-phase water-hydrocarbon cluster dynamics and using machine learning to simulate complex molecular interactions and vibrational spectra. During her PhD, Dr. LeMessurier also interned at Sandia National Laboratories through the DOE SCGSR program, where she developed new strategies to train machine learning interatomic potentials for charged molecular clusters. Collaborating with experimental chemists, her work captured the dynamics of charges and molecular interactions, revealing the fundamental chemistry and physics behind features in the experimental data.

In addition to her research, Dr. LeMessurier is passionate about scientific education and outreach. During her PhD, she participated in multiple outreach organizations, working with middle and high school students on broad scientific projects. Having earned a Certificate in College Teaching and multiple research and presentation awards, Natalie is passionate about translating complex physical chemistry concepts into clear, accessible guidance for aspiring student researchers and developing strong research and communication skills in new scientists.