The successful candidate for this position will perform research to develop innovative approaches to advance new modeling and characterization of physical systems and engineering structures. The work involves development of new dynamic system identification and damage detection algorithms through integration of machine/deep learning and physics models. The successful candidate will exploit a wide class of structural dynamic models (elastic waves, vibrational, thermal, etc) and work with a team with computer scientist/software engineer to develop machine/deep learning based algorithms for structural dynamics identification and health monitoring for a broad spectrum of fundamental physical models and engineering structures.
Extensive knowledge and research experience (Ph.D.) in Civil/Mechanical Structural Engineering and Dynamics (acoustics and/or vibrational, etc);Demonstrated experience in machine/deep learning, signal/image processing, system modeling and optimization.Demonstrated experience in developing techniques (e.g., ultrasonics based on MEMS/laser/PZT, thermography, etc) for nondestructive evaluation and structural health monitoring applications.Programming experience in C, C++, and/or Python. Experience in Keras, Tensorflow, and/or other platforms.Good communication skills both verbal and written.
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