Postdoctoral Researcher in Transportation: Samer Madanat
NYU ABU DHABI
San Francisco, CA
Full-time
Research
Posted on April 1, 2024
Description
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.
Qualifications
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.
Application Instructions
Please submit the following as part of the application:
1. A Cover Letter
2. A recent CV, including a list of publications in refereed journals and conference proceedings
3. The names and contact information for two academic references
Equal Employment Opportunity Statement
For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
NYU is an equal opportunity employer committed to equity, diversity, and social inclusion.
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.
Qualifications
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.
Application Instructions
Please submit the following as part of the application:
1. A Cover Letter
2. A recent CV, including a list of publications in refereed journals and conference proceedings
3. The names and contact information for two academic references
Equal Employment Opportunity Statement
For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
NYU is an equal opportunity employer committed to equity, diversity, and social inclusion.
