Doktorand (m/w/d)

ZF Friedrichshafen AG

Friedrichshafen, BW, DE
On-site
Friction and wear simulation
Machine learning methods
Physics-informed neural networks
Develop a simulation model for the physically correct representation of friction and wear and their resulting influences on the system behavior of chassis components

Job Summary

  • Develop a simulation model for the physically correct representation of friction and wear and their resulting influences on the system behavior of chassis components.
  • Evaluate and further develop established friction and wear models based on existing and to-be-generated experimental data.
  • Integrate design parameters and manufacturing and assembly-related tolerances as a contribution to standardization and increased manufacturing quality.

Matching Summary

Develop a simulation model for the physically correct representation of friction and wear and their resulting influences on the system behavior of chassis components.

Skills & Requirements

Must-have

  • friction and wear simulation
  • machine learning methods
  • physics-informed neural networks
  • support vector machine
  • finite-element analysis

Nice-to-have

  • system behavior analysis
  • robust system design
  • reduce testing effort
  • shorten development times

Key Requirements

  • Master's degree in Mechanical Engineering, Automotive Engineering, Physics, Simulation Technology, Computer Science, Mathematics or comparable
  • Programming skills in MATLAB/Simulink
  • Experience with Machine Learning methods in Python (PyTorch/TensorFlow)
  • Experience in simulation of tribological contacts
  • Very good German and English skills

Work Rights

Not specified

Tailored Resume

Cover Letter