Ford Motor Company Transportation Modelling Engineer: Shared Mobility and Traffic in Dearborn, Michigan

30019BR

Job Title:

Transportation Modelling Engineer: Shared Mobility and Traffic

Job Description & Qualifications:

Job Description

The candidate will play a pivotal role in developing Ford’s transportation operating system (tOS). They will be an integral part of Ford’s \"Mobility Research\" department: a varied and interdisciplinary group within Research and Advanced Engineering that is dedicated to cutting-edge research to improve transportation accessibility, mobility, and sustainability for all. The candidate will help Ford to develop and simulate a variety of new mobility solutions, both for internal customers at Ford and for cities themselves. Specific responsibilities include:

  • Develop and simulate innovative transportation concepts and solutions for cities, such as:

  • Shared Mobility Services

  • Multimodality

  • Transportation Network Resilience

  • Connected and Autonomous Vehicle (CAV) Integration

  • Transportation Planning for Rapid Urbanization

  • Integrate Ford concepts and solutions into traditional and new microscopic and mesoscopic transportation models. Some examples are traffic signal optimization, car-following behavior (including simulating mixed traffic with automated and manually-driven vehicle), and various shared-mobility models.

  • Work with the team and external transportation partners, including commercial companies, universities, national labs, and government (e.g. MPOs and DOTs).

  • Work with various groups within Ford: e.g. Ford Mobility and City Solutions, Strategy, Global Data Insights and Analytics, Automated Vehicles, and Product Development.

Position Qualifications:

Required:

  • Master's degree in Civil Engineering, Urban Planning, Industrial & Operations Engineering (with a focus in transportation).

  • 2+ years’ experience in transportation modeling, including work on one or both of the following (coursework allowed):

  • Hands-on microscopic traffic simulation using software programs such as PTV Vissim, Aimsun, TransModeler, etc. Self-coded approaches also acceptable (e.g. for dissertation work). Focus could be in areas such as traffic signals or car-following.

  • Shared mobility modelling, such as on dynamic shuttles, shared automated vehicles, and/or mobility as a service.

Preferred:

  • PhD. In Civil Engineering, Urban Planning, Industrial & Operations Engineering (with a focus in transportation) or equivalent.

  • Experience in transportation modelling/optimization approaches that deal will “new mobility” solutions. In addition to shared mobility modeling as mentioned above, other examples include connected vehicles (e.g. V2V and V2X), autonomous vehicles, multimodality, transportation accessibility, and journey planning.

  • Experience in mesoscopic activity-based and/or agent-based transportation models, such as MATSim.

  • Experience in mode choice and other aspects of user behavior

  • Experience working with city and government planners

  • Experience with using GIS

The distance between imagination and … creation. It can be measured in years of innovation, or in moments of brilliance. When you join the Ford team discover all the benefits, rewards and development opportunities you’d expect from a diverse global leader. You’ll become part of a team that is already leading the way, with ingenious solutions and attainable products – and it is always ready to go further.

Visa sponsorship may be available for this position.

Ford Motor Company is an equal opportunity employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Auto req ID:

30019BR

Company:

Ford Motor Company

Function:

Product Development

Skill Team:

Research & Advanced Engrg

Sub-Component:

Research & Advanced Engrg

State:

Michigan

Location:

Dearborn