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Postdoctoral Researcher – Multi-resolution Transportation and Energy Modeling

💼 Graduate Job


💻 Remote
🤑 $73.2K - $120.8K

AI generated summary

  • You must have a recent PhD in transportation or computational sciences, with strong skills in transportation modeling, scientific programming, machine learning, and big data analytics. Experience with relevant tools and technologies, GPA over 3.5.
  • You will work on integrating NREL tools into travel demand models, develop travel choice models using traditional and big data sources, perform big data analytics, work on cloud-based web applications, enhance modeling tools, and contribute to publications and research proposals.

Graduate Job

Research & Development, DataGolden


  • Seeking a high-caliber postdoctoral candidate to join our group and to conduct research related to mobility and energy impacts of emerging transportation technologies. Candidates with knowledge and experience in travel demand modeling, travel behavior methods, geospatial analysis, high performance computing, and advanced choice modeling techniques are encouraged to apply. Relevant areas of research the candidate will be working on include: (i) Travel demand modeling, (ii) Econometric and statistical methods for transportation data analysis, (iii) Mobility and energy impacts of disruptive transportation technologies, and (iv) Transportation system efficiency quantification. Prior knowledge in applying traditional (four-step) travel models, and advanced agent-based transportation models is strongly preferred. Application of machine learning techniques to travel behavior modeling is desired.


  • Must be a recent PhD graduate within the last three years.* Must meet educational requirements prior to employment start date.
  • Preferred Qualifications:
  • Familiarity with transportation data and development of travel modeling and forecasting tools.
  • Experience with transportation modeling packages such as CUBE, TransCAD, MATSim, or similar tools.
  • Strong background with scientific programming languages such as Python, R, Rust, or Scala.
  • Strong interest in, and working knowledge of high-performance computing and transportation modeling, with a degree/background in one or the other.
  • Relevant transportation skills may include travel demand modeling, micro-, meso- and/or macroscopic traffic modeling, and transportation energy analysis.
  • Relevant computational skills may include machine learning, deep learning, distributed computing, and big data management/analytics.
  • Familiarity with location-based data, and its use for travel modeling.
  • Knowledge of GIS, GPS, data analysis and visualization, web design, and/or engineering computing.
  • Strong collaboration skills—thrives working in a collaborative team environment but is comfortable working independently when necessary.
  • Additional preferred qualifications:
  • Excellent verbal and written communication skills.
  • Experience with data analytics, big data management, scraping data off the web, high-performance/distributed computing, machine learning and/or deep learning.
  • Application development experience in a general-purpose programming language such as C/C++, JavaScript, Java, Scala, or Rust.
  • Experience interfacing with Metropolitan Planning Organizations (MPOs) and other transportation data and modeling stakeholders.
  • Knowledge of cloud computing services such as AWS, Azure, or Google Cloud.
  • Working with HPC and databases, including PostGres, and slurm.
  • Experience in transportation and/or computational sciences.
  • Experience with collaborative software development and use of Git/GitHub for project management and version control.
  • Knowledge of access theory.
  • Cumulative undergraduate/graduate GPA over 3.5 on a 4.0 scale.

Education requirements


Area of Responsibilities

Research & Development


  • Working with travel demand models, particularly integrating NREL developed tools such as the Mobility Energy Productivity (MEP) metric, and Route Energy Prediction Model (RouteE) into existing travel demand models.
  • Developing travel choice models using traditional (survey) and non-traditional (big-data) sources.
  • Perform big data analytics, visualization, and interpretation.
  • Working with cloud-based web applications and scalable data analysis pipelines, refactoring data science scripts as cloud-native software.
  • Building, enhancing, and validating modeling and simulation tools.
  • Assist in producing high-quality publications, reports, and research proposals.
  • Supporting additional related research projects as needed.
  • .

Application process

  • Please include all relevant experience and qualification information on the uploaded PDF (or MS Word) copy of your resume or CV.


Work type

Full time

Work mode





73200 - 120800 USD