Ihre Aufgaben
You will be investigating new methods to extend the field of possibilities for tire wear estimation, especially for fleet management. Your main responsibility will be to adapt a Virtual Sensor to work on low frequency data as part of an exploration activity.
Key Responsibilities
- Collaborate hand-in-hand with Data-Scientists to support the development of a cutting-edge automotive solution.
- Understand and modify an existing approach to adapt to challenges from low frequency time series typically available for fleet monitoring.
- Imagine,implement and evaluate different approaches for this Virtual Sensor.
- Contribute toan exploratory phase of a Virtual Sensor to shape a new market positioning.
Ihr Profil
- Bachelor or Master student in Mechatronics or Mechanical Engineering, with knowledge of vehicle dynamics and signal processing.
- Proficiency in Matlab/Simulink and Python for data analysis and scripting.
- Strong analytical and problem-solving mindset.
- Interest in innovative automotive technologies development.
- Experience with time-series data analysis is a plus.
