The Postdoctoral Associate will conduct integrated experimental and computational research on informatics-driven mechanical characterization of solid and porous materials, supported by an NSF CMMI CDS&E award and industry-sponsored projects. The primary function of the position is to develop and cross-validate the experimental and numerical platforms of the mechanics informatics framework. On the experimental side, this involves designing and fabricating heterogeneous specimens, conducting multiaxial mechanical tests on a dual-actuator loading frame, and acquiring full-field deformation data using three-dimensional digital image correlation (DIC). On the numerical side, this involves building automated finite element and inverse-identification workflows that learn constitutive parameters from a single informative test through Bayesian optimization, together with quantification of measurement and model-form uncertainty. Approximately half of the effort will extend this framework to the constitutive modeling of porous and cellular materials, such as polymer and metal foams, and to industry-sponsored projects on the mechanical testing and qualification of battery components. The role combines hands-on experimental mechanics with rigorous simulation and data analysis and benefits from complementary expertise in scientific machine learning and constitutive modeling of anisotropic and compressible materials.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree