Postdoctoral Researcher in Transportation Full-time Job

The Post-Doctoral researcher will work with Professor Samer Madanat and his current research team. The focus of this position is the design and development of computationally efficient, data-driven methods for system-wide traffic control in urban areas. The specific application will be to predict traffic flow patterns in urban networks when parts of the network are cut due to inundation resulting from sea level rise (SLR), by using machine learning methods.

Using these models, optimal protection scenarios and traffic control can be used to minimize the negative impacts of SLR.

The candidate must have a Ph.D. degree (or equivalent) in Engineering, Operations Research, Computer Science or related field and is expected to have a strong background and prior expertise in Machine Learning as well as Traffic Modeling in order to pursue multidisciplinary research at the intersection of these two realms.

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