Postdoc position for a computational mechanician in the Computational Physics Group @ University of Michigan

The Computational Physics Group at the University of Michigan has an opening for a postdoctoral researcher in data-driven computational mechanics. This position can be available as early as July 1, 2022. Research in the Computational Physics Group is focused on developing data-driven, machine learning and some artificial intelligence approaches that interact with a range of computational methods for problems in materials physics, biophysics and in engineering more broadly. The individual who joins the group for this position also will have the opportunity to work on a range of scientific machine learning and data-drive techniques that we develop. These will include neural networks-based solvers of PDEs, graph theoretic methods for reduced-order modelling, system inference and machine learning for bridging scales in materials, among others--all in the context of the above computational physics applications. For our recent research in these areas, please follow this link to the Group’s publications.

A PhD in engineering, applied mathematics, biophysics or applied physics is required. Expertise in computational mechanics, and scientific computing, as well as an exposure to data-driven modelling are desired. Please respond with a CV and a statement of research interests to Krishna Garikipati (krishna@umich.edu).

The University of Michigan, and the Computational Physics Group are committed to a just and inclusive treatment of all, regardless of backgrounds of race, ethnicity, gender orientation, sexual orientation, age and other demographic markers.