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Thesis Work: Streaming Inference and Provenance on Vehicular Hardware

Let's create the future together.

At Volvo Cars, we believe that being curious and truly committed to understanding people is the key to future success. We are people who care about other people, working together to create new technologies and innovations for safe, sustainable and convenient mobility. Want to join us?


Data Streaming is a key paradigm for dealing with high volumes of real-time data, such as that produced by the sensors of an autonomous vehicle. In such vehicles, a complex analysis pipeline stretches from the raw sensor data to an actionable prediction, often achieved using Machine Learning. Being able to trace back to the raw sensor data ultimately responsible for that prediction is valuable for targeted data gathering. In this project, the goal is to implement such a back-tracing mechanism (called provenance) on vehicular hardware.

This thesis work will include the following tasks:


  • Deploying a Machine Learning model on vehicular hardware (NVidia Jetson)
  • Embedding Machine Learning inference on Jetson with a Stream Processing Engine (SPE)
  • Implementing the backtracing mechanism
  • Benchmarking the performance of the system using real-world data
  • Combining this system with an experimental algorithm for driver pose estimation developed in another thesis work
  • Documenting the results in a thesis report and making a final presentation. Any source code that is developed should be well-documented and annotated.


The candidate should be in the final phase of a Master of Science Computer Engineering or similar program, ideally have some experience programming in Java, ideally have worked with Stream Processing and / or Machine Learning before.


Starting date: The candidate is supposed to start on April 6th 2020.
The duration of the project is 6 months, and could be extended if needed.
Number of students: The project is suitable for 1 student.

For the duration of the project, you will be working in the Big Data team at Volvo Cars, on the forefront of data analysis technologies in the vehicular world. The work will be done in close collaboration with the Distributed Computing and Systems group within the Network and Systems Division at the Computer Science and Engineering Department of Chalmers University.


Attach your resume and cover letter stating your interests within the given area and your thoughts and credentials. Please note that applications arriving later then the last application date will not be taken in consideration. Selection will be ongoing during the application period. We want your application as soon as possible, but no later than 2020-02-28. Please note that applications via email will not be accepted.

Contact Details
If questions regarding this thesis work, please contact Bastian Havers, bastian.havers@volvocars.com

Please contact Vincenzo Gulisano for academic requirements prior to applying to this thesis project, vincenzo.gulisano@chalmers.se



Who are we?

Everything we do starts with people. Our purpose is to provide freedom to move, in a personal, sustainable and safe way. We are committed to simplifying our customers’ lives by offering better technology solutions that improve their impact on the world and bringing the most advanced mobility innovations to protect them, their loved ones and the people around them. 

Volvo Cars’ continued success is the result of a collaborative, diverse, and inclusive working environment. The people of Volvo Cars are committed to making a difference in our world. Today, we are one of the most well-known and respected car brands, with over 40,000 employees across the globe. We believe in bringing out the best in each other and harnessing the true power of people. At Volvo Cars your career is designed around your talents and aspirations so you can reach your full potential. Join us on a journey of a lifetime as we create safety, autonomous driving and electrification technologies of tomorrow.

Gothenburg, SE

Job requisition ID:  33529

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