There is an immediate opening for a postdoc position in my research group in the School of Natural Sciences at the University of California, Merced. The postdoctoral researcher
will work under an NSF-funded Collaborative Research (with UC Merced, UT Austin and MIT) entitled: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion (see https://hippylib.github.io for a general overview of the project).
This project involves research in the field of large-scale Bayesian inverse problems, and in particular on implementation work on adding new features in hIPPYlib (https://hippylib.github.io). hIPPYlib contains implementations of state-of-the-art scalable adjoint-based algorithms for PDE-based deterministic and Bayesian inverse problems. It builds on FEniCS for the discretization of the PDEs, hence all the code development tasks are tight to being able to work with FEniCS and on python coding experience. There will be occasional C++ implementation needs as well, hence experience with C++ is a plus.
The postdoc will contribute to the research dissemination and will also help build the user/developer community by attending and speaking at conferences, workshops and summer schools at local and international events.
Interested candidates should contact Noemi Petra at npetra at ucmerced.edu and apply at: