Postdoc Position in Uncertainty Quantification Available

We seek applications for an open postdoctoral position available in the research group of Prof. Alison Marsden at Stanford University, in collaboration with Daniele Schiavazzi at Notre Dame, in the broad research area of model-based inference with applications to cardiovascular hemodynamics. The candidate will be responsible to conduct methodological and applied research, participate and help to organize research group meetings focusing on the solution of direct and inverse problems in uncertainty analysis and the construction of multi-fidelity surrogate models.

We are seeking a highly motivated and driven applicant with strong writing and communication skills, a strong background in applied probability and uncertainty quantification, computational fluid/solid mechanics, coding in C++/Python, and the ability to work independently and collaborate effectively. Previous experience with parallel programming (CPU/GPU) and development of deep learning neural networks in PyTorch is a plus.

The position will initially be for one year with the possibility of extension depending on performance.

To apply, submit a cover letter explaining your interest in the position, CV, and at least three letters of recommendation. The evaluation of candidates will begin immediately and continue until the position is filled.

Application Materials Required:
Cover Letter
Curriculum Vitae
Three Reference Letters
Please submit as a single PDF to amarsden@stanford.edu