The successful candidate for this position will perform non-destructive evaluation (NDE) research in developing new ultrasonic sensing and analysis approaches to advance modeling and characterization of complex engineering structures/materials (e.g. composites). The work involves development of new algorithms through integration of machine/deep learning and physics models. The successful candidate will also collaborate with scientists at Argonne National Laboratory (https:www.anl.gov) and Los Alamos National Laboratory (https://www.lanl.gov/).
Doctoral Degree in Mechanical/Civil/Electrical/Aerospace/Industrial Engineering
Experience in machine/deep learning, signal/image processing, optimization, networks, or other related expertise.
Demonstrated experience in developing/applying techniques (e.g., acoustics/ultrasonics, thermography, optics, etc, or other related domains/tools) for nondestructive evaluations, structural health monitoring, additive manufacturing, or any other related engineering or mechanics-related applications.
Programming experience in Python or C/C++, or related. Experience in Keras/Tensorflow, or any other related platforms.
Good communication skills both verbal and written.
The position is available immediately and requires a start date no later than early Spring 2022. Candidates with exceptional qualifications will be considered for the rank of Research Scientist. Send CV to Prof. Yongchao Yang (firstname.lastname@example.org), and qualified candidates will be contacted.
About the PI – Dr. Yongchao Yang is an Assistant Professor in the Department of Mechanical Engineering – Engineering Mechanics at Michigan Tech. He was a Staff Scientist at Argonne National Laboratory (2018-2019), after a Director’s Funded Postdoctoral Fellowship at Los Alamos National Laboratory (2015-2017). He obtained his Ph.D. from Rice University in 2014 and bachelor’s from Harbin Institute of Technology in 2010, both in structural engineering. His expertise is in structural dynamics, experimental mechanics, system identification and health monitoring. His recent research, funded by DARPA and DOE, has focused on developing new high-resolution structural sensing/imaging and identification methods, combining approaches from computer vision and machine learning. He is the author of more than 40 international journal publications, 3 book chapters, and 2 US patents. Find out more about Dr. Yang’s recent publications, sponsored projects, awards and recognitions in his webpage (https://www.mtu.edu/mechanical/people/faculty/yang-y/).
Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer that includes providing equal opportunity for protected veterans and individuals with disabilities.
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