Opportunity at Federal Highway Administration (FHWA)
Use of Data Science in Asphalt Materials
Federal Highway Administration
||McLean, VA 221012296
|Maryam Sadat Sakhaei Far
The Federal Highway Administration's Turner-Fairbank Highway Research Center (TFHRC) is seeking a postdoctoral associate with an expertise in applying machine learning to asphalt materials. The ideal candidate possesses specialized experience with respect to:
- Laboratory evaluation of asphalt materials (mixture and binder preferred);
- Relating field performance data to the laboratory-measured data for asphalt materials;
- Data mining and database management;
- Developing and interpreting artificial neural network approaches to model behavior of asphalt materials; and
- Understanding of performance specifications and the role of volumetrics and component materials in long-term pavement performance.
The use of machine learning offers potential to the asphalt pavement community. Additionally, TFHRC offers a unique dataset to advance this important topic, including but not limited to performance information from the Long-Term Pavement Performance database and the Asphalt Binder and Mixture Laboratory (ABML) at TFHRC. Possible applications include characterization of emerging technologies and additives, optimizing construction processes, and long-term pavement performance prediction. The associate will be expected to advance FHWA's goals in data science applications to asphalt materials.
Machine Learning, Artificial Neural Network, Laboratory Evaluation, Pavement Performance Models, Asphalt Concrete
Open to U.S. citizens, permanent residents and non-U.S. citizens
Open to Postdoctoral and Senior applicants
Postdoctoral and Senior Associates will receive an appropriately higher stipend based on the number of years of experience past their PhD.