We are looking for a talented individual to join our research team and contribute to the development of machine learning methods for testing battery and fuel cells.
Job Description
Fitting physical models to test measurements is a powerful tool in capturing the inner characteristics of batteries and fuel cells. However, the fidelity of these models depends on the set of physical phenomena covered by mathematical formalism. In contrast, data-driven models like artificial neural networks do not require prior electrochemical knowledge and rely entirely on the data collected during testing.
* Development of machine learning algorithms for testing purposes
* Implementation of these algorithms into our testing pipeline
* Overcoming limitations of sparse and out-of-distribution training datasets
Benefits:
* Ongoing studies in Computer Science, Telematics, Physics or Electrical Engineering
* Good programming skills in Python or C++
* Knowledge of Machine Learning
* Good knowledge of English and German
* Skills in solving PDEs are beneficial
* Presence at our headquarters is required
What We Offer:
* A unique opportunity to work with experts in the field and gain practical experience
* The chance to exchange ideas and learn from colleagues
* A stimulating work environment that encourages innovation and creativity