Work environment

Combine engineering science with cutting-edge AI to shape the dynamic world of electric drive systems and turn data into groundbreaking innovations! We work in an exciting environment focused on the technical development of powertrain and energy systems for the Volkswagen brand group core. As part of the pre-development, we develop innovative drive concepts for battery-electric and hybrid vehicles. Our team plays a crucial role, as we focus on the data protection-compliant collection, processing, and analysis of data from potentially all customer vehicles worldwide. This leads to an enormous amount of data, which we utilize on scalable platforms with artificial intelligence technologies. We are interested in questions such as: What are our customers' needs? How are the vehicles used? Which functions are particularly in demand and which components are particularly stressed over the course of the vehicle's life? With these insights, we drive data-driven product development and optimization. Our goal is to develop vehicles based on the data collected that are not only better and more reliable but also more cost-effective. As part of this PhD program, an AI model is to be developed that builds a deep, semantic understanding of vehicle data. The goal is to recognize, abstract and represent typical usage patterns or trends from large-scale data collected from customer vehicles in the form of a virtual customer base. This virtual customer base should be able to represent, classify and, if necessary, synthetically generate real customer behavior - for example, for specific driving styles or environmental conditions.

Possible Tasks within this Role

• Developing an AI model with semantic understanding of vehicle data using state-of-the-art models or methods
• Evaluating and testing various solution concepts for the "virtual customer base"
• Conducting in-depth analyses of vehicle data to answer a wide variety of engineering questions, as well as preparing and presenting results for various stakeholders
• Optimizing the handling of big data on scalable platforms

The final doctoral topic is defined together with the professor. The prerequisite for the cooperation is the confirmation of supervision as well as a confirmed delimitation of topics by the professor of a university or research institution entitled to confer a doctorate.

Qualification requirements

• Good to very good university degree qualifying for doctoral studies in the field of computer science or engineering disciplines
• Very good programming skills (especially Python)
• Practical experience in the field of artificial intelligence (AI)
• Experience with big data and scalable systems (e.g., Apache Spark) would be helpful
• Independent and structured working style
• High level of motivation
• English language level B2

Keywords

Dissertation, GPT, Deep Learning, E-Mobility, Data Science