At the forefront of life, technology, and many areas of research, computational methods are consistently increasing in applicability and power. A key focus of my research is linking together different scales and disciplines in science. My bachelor's work used density functional theory to study fundamental reactions in organic synthesis (Seitz et al, JOC 2016). This chemistry background formed the basis of my PhD work, where my applications shifted to basic biology and global diseases. I used elastic network models to study plant respiration (Takahashi et al, Sci. Adv. 2022) and prokaryotic "proto-nuclei" (Laughlin and Deep et al, Nature 2022). I also extensively studied molecular recognition in influenza through Brownian dynamics (Seitz et al, Biophys. J. 2020), molecular dynamics and Markov state models (Casalino et al, ACS Cent. Sci. 2022). Finally, I went back to my density functional theory roots for a measles drug discovery project (Ahn and Seitz et al, DIB 2021). Bringing forward my newfound skills in biophysics along with my chemistry training, my postdoc work is on artificial intelligence in viruses and vaccine development.