Intern Tire Wear (m/f/d)

a paid-position in Darmstadt

Your mission

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.

Your profile

• 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.