Opportunity at Federal Highway Administration (FHWA)
Use of Data Science in Asphalt Materials
Federal Highway Administration
||McLean, VA 221012296
|David Jonathan Mensching
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.
Artificial neural network; Machine learning; Pavement performance; Pavement prediction; Laboratory evaluation; Asphalt concrete; Asphalt mixture; Asphalt;
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.