Job Title: Feasibility Study of a Reduced Order Model for Calculating FFR Using Angiographic Data - Postdoctoral position

Location of Position: Ann Arbor, Michigan

Employing Institution: University of Michigan

Description of Position: Alberto Figueroa and Krishna Garikipati at University of Michigan are recruiting a post-doc to work on an NSF-funded STTR project. The research involves machine learning, specifically graph-based methods for reduced-order modeling of vascular flows. This project is in partnership with the start-up company AngioInsight. 

In addition to working in close collaboration with AngioInsight, the successful candidate will also work closely with our team of clinical collaborators Venk Murthy and Brahmajee Nallamotthu at the University of Michigan Medical School.

We are very interested in attracting the best candidates from the computational mechanics community.

Minimum Qualifications: Qualified candidates will have expertise in computational mechanics, applied math, and machine learning. Familiarity with programming languages, C++ and Python, and with open-source machine learning frameworks such as TensorFlow, Keras or PyTorch will be desirable.

Application Procedure: To apply, please send a CV and a couple of references to [email protected] and [email protected]

Contact Information: Krishna Garikipati, [email protected] or Alberto Figueroa, [email protected]

Website: For more information on the collaborating groups please visit the Computational Vascular Biomechanics Lab and The Computational Physics Group

Closing Date: 8/15/2022