Machine Learning

Want to know what holds your car together? Modern cars contain tens of thousands of solder joints in up to 150 electronic control units. Under the most adverse operating conditions, the solder joints in cars are supposed to last for years and ensure that, for example, LED headlights or sensors for autonomous driving take us safely to our destination. In our current research project MaWis-KI, you will find out how solder joints change during their lifetime. Ultrasonic microscopy, X-ray images, thermomechanical analyses and FEM simulations are available as data sources.

You combine this data with the latest machine learning methods to develop sustainable electronics for the vehicles of the future. In an agile and young research team, you help to research on the lifetime prediction of electronic components with machine learning. Your focus will be on building the infrastructure and pipeline for data acquisition, storage, and pre-processing. You will learn how machine learning projects are professionally implemented and you will have the opportunity to develop yourself and your skills.

We are interested in a long-term cooperation and are extremely flexible regarding timing of internships and working student activities.

Would you like to have a look here?

Find out more about us and your application.