R&D Associate Staff Member - Freight and Passenger Transportation Modeling
The Transportation Analytics & Decision Sciences Group (TADS) is seeking to fill an Associate Research Staff position with a focus on freight demand and intermodal movement. The successful candidate will be able to work with a research team from various backgrounds using a variety of sources to estimate freight flows on a national scale including imports and exports. The team is also seeking assistance in passenger travel as well, including household travel behavior and travel in urban environments.
TADS goal is to find sustainable multi-modal (air, land, water, pipelines) solutions to passenger and freight transportation challenges within the broad context of environmental, social, and economic goals. Research teams apply statistical and econometric modeling, machine learning, simulation, and optimization methods to data-intensive analyses. The resulting data sets and models seek to illuminate historical performance of the transportation system with multiple metrics, to predict future performance under various scenarios, and to search for optimal pathways to sustainable futures.
For additional information on the Transportation Analytics & Decision Sciences Group, click on the following. URL: https://www.ornl.gov/group/transportation-analytics-and-decision-sciences
Job Duties and Responsibilities:
You will collaborate with ORNL staff from various groups who are experts in technical areas such as transportation demand modeling, electrification of transportation modes, renewable energy production, energy storage, and electricity distribution. You will seek out data sets for specific commodities, analyze the validity of the data, and estimate inter-regional flows. You will use your skills to manipulate large datasets, develop analyses, and model transportation flows in multiple projects.
- Participate in modeling and analysis efforts with the Freight Analysis Flow team
- Participate in analysis and application development studies with the National Household Travel Survey analysis team
- Participate in other transportation planning/policy analysis and application development projects as needed
- PhD in transportation engineering with a recognized record of research accomplishments.
- At least two years of experience in an applied transportation analysis and modeling position.
- Strong understanding and working experience of freight network and commodity flows.
- In-depth knowledge and proven working experience with public data sources for transportation planning and relevant fields, including CFS, FAF, CBP, TMAS, and NHTS.
- Background experience and current field of study should have an emphasis on freight planning and transportation systems including modeling, simulation, and development of algorithms for trip generation and distribution models.
- Proficiency in the use of modeling and simulation tools, such as MATLAB, R, and Python.
- Excellent oral and written communication skills to support regular interactions with ORNL staff, management, sponsors, and others, and to prepare reports, publications, and journal articles.
- Advanced degree in mathematics or statistics is highly preferred for consideration due to the importance of the job duty on such model developments on both theoretical and practical aspects.
- Knowledge and working experience of programming skills (e.g., C++, Java, and VBA), as well as advanced skills in use of statistical software (e.g., SAS, SPSS, and JMP) and GIS tools (e.g., ArcGIS, TransCAD), for transportation related projects.
- Demonstrated ability to execute data mining, web scraping, and handling big data.
- Experience in safety analysis for transportation.
This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.
If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.
ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.