Sarah McFann is pursuing a PhD in chemical and biological engineering at Princeton University.
Currently, she studies how cells interpret biochemical signals to make decisions. She uses both mathematical and experimental techniques, including numerical simulations, parameter estimation, live imaging, genetics, and optogenetics. Her PhD thesis looks at how cells in the fruit fly embryo interpret growth factor signaling differently depending on when and what level of signal they see, which helps determine what type of tissue (muscle, gut, nervous system, etc.) a cell will become.
She is especially interested in how math modeling and computational techniques can be used to better understand the mechanisms underlying cellular behaviors. She has used math modeling to improve understanding of how cancer mutations affect signaling and to help design a high-throughput method for detecting dynamic signaling events in living cells. During a PhD internship at the Bill & Melinda Gates Foundation, she used math modeling to help convert data on infant growth, immunity, and the gut microbiome into global health interventions.
Sarah received her BS in chemical engineering from the University of Alabama. As an undergraduate, Sarah developed computational cellular models to aid in the optimization of bacterial cells for biobutanol production and designed and built an automated iPad-based microscope and app to inexpensively and effectively track tissue development.
When she isn’t at the microscope or running simulations, Sarah enjoys writing. In addition to science communication, she writes fiction and creative nonfiction.