Our mission has started. We are starting our own battery cell production in Battery Valley in Salzgitter and ramping up our headquarters for global cell production. A key factor in scaling up battery cell production is the manufacturing of prototypes, which ensures the manufacturability of new cell designs. Data analytics plays an important role in evaluating the manufacturing processes by enhancing the understanding of the complex cause-and-effect relationships in battery cell production. This thesis aims to develop machine learning models that capture these relationships based on data from pilot line production. The models will enable predictive analytics for optimizing product quality and process settings, ultimately accelerating process development.

• Analyze the state of the art of machine learning in battery cell production and identify potential use cases
• Identify relevant process parameters, material properties and product properties for the selected use case
• Establish data pipelines for acquisition and preprocessing of production data
• Augment existing data through the generation of synthetic or experimental data
• Develop and validate machine learning models to predict key product properties
• Create a tool based on user requirements to leverage the machine learning models

• Currently pursuing a degree in Information Technology, Engineering, or a related field
• Initial experience with statistical analysis, data modeling and machine learning
• Familiarity with programming languages such as Python, SQL, or similar
• Strong analytical and problem-solving skills
• Excellent communication and teamwork abilities
• Fluent in German and/or English, both written and spoken

• Diverse work environment with strong team-spirit
• Project ownership through which you can actively take part in shaping the future of e-mobility
• Health and wellness programs
• Regular social events
• Corporate Benefits