Franziska Seeger

Franziska is a protein biophysicist turned computational protein engineer, passionate about applying computational modeling and machine learning to develop the next generation of biologics. During her PhD at the University of Maryland Baltimore County and Lawrence Berkeley National Laboratory, Franziska elucidated the activation mechanism of a crucial drug target for cardiovascular diseases. Her fascination with proteins and protein-protein interactions led her to pursue a postdoc with David Baker at the Institute for Protein Design, where she engineered two of the first de novo minibinder inhibitors against autoimmune disease targets.

Franziska’s diverse experience spans consulting on protein biophysics and protein design through her own agency, to working at the intersection of protein engineering and machine learning at Amazon and Novo Nordisk. In 2022, she joined Machine Learning and Drug Discovery (MLDD) at Genentech, where she leads a team at the interface of structural and computational biophysics, machine learning, and antibody engineering. Her current focus is on solving the de novo antibody engineering challenge.

Outside of work, Franziska enjoys spending time outdoors with her dog and horse, engaging in activities such as running, mountain biking, backcountry skiing, and hiking/backpacking. When indoors, she practices yoga, teaches meditation, and enjoys reading.