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Traffic Engineer - Paid Internship

Miovision

Remote

01.12.2021.

praksa nepuno radno vreme dostupno studentima online intervju za posao

If you are passionate about road transport, traffic engineering, traffic signals, planning, and optimization, join us as a Traffic Engineering intern. You will work on cutting-edge software for real-time traffic data prediction in US cities and prepare the environment for the next stage of autonomous vehicles and connected cars.   

Your main mission will be to facilitate the process of optimizing traffic signals in the US. Our goal is to build optimal machine learning models that will enable us to develop timing plans for entire traffic signal networks that outperform current adaptive technologies and human-driven optimizations. Your work will impact millions of people every day!

You can expect to:

  • Work on innovative products/projects, always pushing boundaries
  • Work with latest tools and technologies
  • Learn about the development of cutting edge AI algorithms from a traffic engineer’s perspective
  • Learn everything about the signal operation, vehicle detection, troubleshooting issues, smart automatization, and optimization
  • Research literature, create presentations, propose ideas
  • Learn about simulations and reinforcement learning in traffic
  • Have a dedicated experienced mentor/s
  • Acquire work experience, learn about teamwork and being agile, including sprints, attending daily meetings with mentors and other team members, monitoring performance, etc.
  • Work remotely, online, from the comfort of your home in a friendly and positive atmosphere!
  • Improve your communication and teamwork skills, get out of your comfort zone.

With your mentor/s you will:

  • Receive extensive training on traffic operations and signal timing and vehicle detection, with an emphasis on Automated - Traffic Signal Performance Measures (ATSPMs)
  • Apply what you have learned in college to real-life situations
  • Learn about Applied Mathematics in Traffic Engineering, Data Science, Machine Learning, and AI
  • Research scientific papers and articles, discuss findings from the literature, and apply them to optimize models and algorithms
  • Create short reports and presentations for the company management
  • Learn how to use state-of-the-art ATSPM software to monitor and evaluate traffic signal performance
  • Explore and use modern tools for traffic analysis and optimization
  • Work with the Data Science team to develop and implement machine learning algorithms and models
  • Have daily meetings and brainstorming sessions 

Qualifications:

  • Currently a BSc or MSc student of the Faculty of Transport and Traffic Engineering (any of the three Road Traffic -Departments). Higher Grade Point Average (above 9.00) will be considered as an advantage.
  • Solid understanding of basic traffic signal operation and traffic concepts
  • Fluency in English (both oral and written). Interns should be able to read and comprehend scientific documentation and literature
  • Familiarity with MS Office tools (Word, Excel, and PowerPoint)
  • Strong communication and teamwork skills
  • Out-of-the-box thinking
  • And most importantly, passionate about learning new things, gaining experience, acquiring new skills

What we expect from you:

  • You are able to start at the beginning of December or January
  • At least 3 months commitment
  • Openness for Flexible working hours, working 6-8 hours per day (we can offer more flexible arrangements when the exams start)

Please submit resumes and cover letters in English. Participation in the internship does not guarantee that you will be offered a full time position.

    Miovison (Traffop doo)

    Miovision provides cities with modern tools to fix today's traffic problems. We offer solutions that collect multimodal traffic data and uncover actionable insights, helping municipalities get more out of their road network. The result: streets capable of moving more people – safely and efficiently – whether they are in a car, on a bus, on a bike or e-scooter, or walking. Since 2005, our systems have counted more than nine billion vehicles around the world. Our head office is located in Kitchener,…

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