"Postdoctoral Associate"

Minimum Education and Experience

The ideal candidate will hold a Ph.D. in Structural Engineering with a strong background in AASHTO-based bridge design, evaluation, and load rating, including experience with LRFD and MBE provisions, reliability analysis, probabilistic modeling, and capacity and demand assessment. Extensive experience with WIM technologies, truck load characterization, fatigue analysis of steel bridges, and data-driven reliability and load rating methodologies is strongly preferred. Experience with FE analysis using commercial software packages such as ABAQUS and LS-DYNA is highly desirable. Knowledge of machine learning (ML) and large language models (LLM) and experience with SHM systems, sensor technologies, model updating, and long-term performance monitoring are desirable. In addition, candidates with experience in advanced laboratory testing of concrete materials and structural members, as well as field implementation of advanced concrete technologies in bridges and infrastructure, are highly desirable. The selected candidate(s) will work closely with other researchers within the RIME Research Group and with partners at the USDOT Tier 1 University Transportation Center, C2SMARTER, led by New York.