Physics enhanced machine learning for vibration prediction of wind turbine gearboxes
Antwerpen, Antwerp, BE, 2600
Req ID 79252 | Antwerpen, Belgium, ZF Wind Power Antwerpen NV
Job Description
What´s Next? Join ZF!
ZF is a global technology company supplying systems for passenger cars, commercial vehicles and industrial technology, enabling the next generation of mobility.
ZF allows vehicles to see, think and act. In the four technology domains of Vehicle Motion Control, Integrated Safety, Automated Driving, and Electric Mobility, ZF offers comprehensive product and software solutions for established vehicle manufacturers and newly emerging transport and mobility service providers. ZF electrifies a wide range of vehicle types. With its products, the company contributes to reducing emissions, protecting the climate and enhancing safe mobility.
It is time to take the right path into your future. With ZF, a leading global technology group.
We are looking for interns for ZF Wind Power in our location in Antwerp, starting as soon as possible for the next six months.
Your tasks as an intern or thesis student in the noise and vibration research and development team:
- Simulation of the dynamic behavior of gearboxes using data driven (machine learning) and physics based (multi-body) models.
- Research on new techniques to enhance data driven models with physical knowledge or vice versa.
- Evaluation of developed approaches with respect to their robustness and potential for generalization.
- Implementation of Gearbox Digital Twin functionality and automated calculation tools for gearboxes
Your profile as an intern or thesis student in the noise and vibration research and development team:
- Study in Mechanical Engineering (major), with a specialization in Data Science or comparable field of study.
- Programming skills (Python), first experience with machine learning and very good English skills.
- Basic knowledge of drive train and gear technology is an advantage.
- Basic knowledge and/or first experience with multi-body modelling is an advantage
- Team spirit, analytical skills, quick comprehension, solution-oriented and independent working style.
Join our ZF team as an intern (m/f/d) and apply now with your complete application documents by sending a mail to lucie.radova@zf.com
Please make sure to send your tabular curriculum vitae and your certificates with your mail.
Be part of our ZF team as Physics enhanced machine learning for vibration prediction of wind turbine gearboxes and apply now!
Contact
Lucie Radová
+420 373 736 426
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Physics, R&D Engineer, Mechanical Engineer, R&D, Science, Engineering, Automotive, Research