AVL is the world's largest independent company for development, simulation and testing in the automotive industry, and in other sectors. As a global technology leader, AVL provides concepts, solutions and methodologies in the fields of e-mobility, ADAS and autonomous driving, vehicle integration, digitalization, virtualization, Big Data, and much more.
Thesis - Data-driven Machine Learning Approach for Li-Ion Battery Ageing in Electric Vehicle Applications
- Conduct literature study on exiting machine learning approaches for battery lifetime estimation
- Review literature approaches in view of their feasibility and computational-efficiency in dealing with battery health in real-world applications
- Develop methods, tools and processes to estimate and predict the degradation behavior of batteries using an data-driven machine learning approach
- Validate your approach for real-time battery health management
- Bachelor's degree in technical or natural science studies (computer science, physics, mathematics or similar)
- Strong proficiency in Python
- Basic knowledge in data-driven approaches
- Experience in applying data science methods is a plus
- Highly developed quality awareness with strong attention to details
- High level of self-reliance with the ability to work in a team, as well as autonomously
- Fluent English language skills are essential, fluent German is beneficial
Vergütung: Der erfolgreiche Abschluss der Diplomarbeit wird mit einem einmaligen Honorar von EUR 2600 brutto vergütet. Laut dem Österreichischen Ausländerbeschäftigungsgesetz ist es leider nicht möglich Diplomarbeiten an Drittstaatsangehörige (nicht EU-Bürger) und Kroatische Staatsbürger zu vergeben, die an einer ausländischen Universität studieren.
AVL is not just about cars. It's about changing the future. Together.