2020-on | Postdoc in Eco-Evolutionary Bioinformatics | Carnegie Institution for Science
2015-2020 | PhD in Bioinformatics and Computational Biology | University of Idaho
2011-2015 | BSc in Botany with minor in bioinformatics | Miami University
Megan received her PhD in Bioinformatics and Computational Biology at the University of Idaho where she focused on performing simulation-based model inference using machine learning algorithms in areas ranging from demographic inference and phylogenetics to community-wide assembly mechanisms. This research was concentrated on disjunct plants of the Pacific Northwest temperate rainforest, but also focused on community-wide plant ecosystems, such as island plant communities. Megan is interested in continuing to apply machine learning algorithms to novel problems in evolutionary biology that can aid in solving our world’s most challenging problems. In the Moi and Rhee labs, she continues to investigate these algorithms to study the relationship between genetic adaptation and response to stress in economically and agriculturally important crop plants. Investigating such adaptations to stress aid in our struggle to understand the future impacts of climate change.