Prof. Victor Zavala has announced an opening for a postdoctoral position in his lab at the University of Wisconsin-Madison. The position is part of an existing NSF project: “Data-Driven, Multi-Scale Design of Liquid Crystals for Air Contaminant Sensing.”
The project aims to develop machine learning techniques that enable the efficient use of large sets of experimental and first-principles simulation data to understand multi-scale phenomena that govern the response of liquid crystals. Such insights are being used to inform the design of ultra-sensitive air contaminant sensors.
The successful candidate will work with a research team that integrates computational expertise (machine learning, density functional theory, and molecular dynamics) with experimental expertise (soft materials and environmental chemistry).
The desired background is flexible. Potential candidates should consider applying if they have a PhD in process systems engineering or computational materials and are interested in obtaining further training in machine learning and its integration with first-principles simulations.
For more information about the position, please contact Dr. Zavala at email@example.com.