Your browser cookies must be enabled in order to apply for this job. Please contact if you need further instruction on how to do that.

Lead Research Scientist, Intelligent Traffic Management

Intelligent Computing Division | Mountain View, CA | Full Time

Job Description

Position Summary

We are seeking a Lead Research Scientist for our R&D group that develops the foundational technologies for our Connected-Vehicle Services.  The selected candidate will lead research projects on connected-vehicle services and develops technologies for intelligent traffic management for connected vehicles.


Primary Performance Responsibilities:

  • Lead the research project on intelligent traffic management for connected vehicles
    • Develop multi-scale traffic management technology for connected vehicle by applying latest intelligent computation technologies such as deep learning.
    • Proof-of-Concept Implementation with simulators


Experience/Skills Required:

  • PhD in Computer Science or a similar field. (Other fields will be considered with relevant experience)
    • Specialty in traffic management and machine learning.
  • 3+ year experience in traffic management research.
  • Experience on leading research projects. 
  • Deep knowledge on intelligent computing technologies including machine learning, and experience on applying intelligent computing technology to traffic management.
  • Knowledge and experience on traffic simulator and strong C/C++, Java, and Python cording skill.
  • Excellent analytical ability and problem solving skills.
  • Ability to learn and willingness to work in a fast-paced unstructured environment.
  • Detail oriented with the ability to work independently.

About us:

Since 2001, Toyota InfoTechnology Center USA, Inc. has specialized in R&D and business research with a focus on cutting-edge information technologies to advance the driving experience of Toyota automobiles and safety of the automotive industry on the globe. ITC’s current areas of interest include future vehicular network,in-vehicle software and system architecture, vehicle-to-vehicle communication technology, intelligent computing technology including artificial intelligence and machine learning.