Stanford University and the University of Colorado, Boulder have multiple immediate openings for postdoctoral positions in scientific machine learning. The successful candidates will join the INSIEME PSAAP Center at Stanford and work with Profs. Eric Darve and Alireza Doostan, alongside a team of experts from both institutions.
The primary focus of the positions is to conduct fundamental research in the areas of uncertainty quantification, data-driven modeling, and machine learning, with a specific emphasis on multi-fidelity modeling, deep neural networks, transfer learning, generative modeling, and inverse problems.
The positions are initially for two years, subject to annual review at the end of the first year. The successful candidates will work on large-scale, multi-physics modeling of complex systems and their HPC implementations.