Master Thesis - Artificial Intelligence - Anomaly Detection in Time Series Data in Köln bei TOYOTA GAZOO Racing Europe GmbH

Do you want to put all your theoretical knowledge into practice, gain operational experience and broaden your skills? We offer a option for you to work with our employees, experts and specialists in a fascinating high-tech environment. We are offering a unique opportunity to prove and recommend yourself for a possible future employment.

The AI/ML Team in TGRE is a highly focused and one of the few teams in the world, which focus entirely on the application of AI and ML in the race environment. Our tools are state-of-art and we have close cooperation’s with the leading institutes in data science. We are passionate and diverse ML engineers who drive to contribute to Toyota victories on the race track.

Your thesis:

During races a large amount of data is generated which needs to be analysed after and/or during the race. This takes a lot of effort of the engineers. By automating the process of detecting anomalies on the data and flagging them to the engineer, more data can be analysed in a shorter period. The goals of this thesis are (1) to implement different anomaly detection methods for time series data and (2) benchmark the different methods in regards to the given performance KPIs.

The successful candidate will have:

• A Bachelor’s degree in engineering, informatics, physics, or related fields
• Courses and student projects with ML in Python, with a particular focus on time series
• Ability to communicate with engineering and technicians from various disciplines
• Well-structured and systematic research approach
• Very good command of the English language (in speech as well as in writing)
• Passion for motorsport