Master Thesis (f/m/x): How EU Tariffs on Chinese EVs Affect German OEMs and Electrification

The Institute of Vehicle Concepts (FK) of the German Aerospace Centre (DLR) is internationally recognised for the design of future road and rail vehicles that enable climate and environmentally friendly mobility while being affordable and user-friendly at the same time.

We research and demonstrate the required key technologies and maintain close cooperation with other scientific institutions as well as industrial and political bodies.

What to expect

Your work will involve investigating how the EU’s November 2024 countervailing tariffs on Chinese battery electric vehicles (BEVs) have influenced the sales dynamics, substitution effects, and environmental impact of new vehicle registrations in Europe.

You will be supported by Timm Höfer (TUM & McKinsey), an expert on EU-level automotive economics and value chains, and Gabriel Möring (DLR), who specializes in vehicle choice modeling across Europe. The core focus lies in quantifying short-term effects on BEV sales, especially of Chinese models, and understanding whether such trade measures support or hinder decarbonization and industrial policy goals.

The research compares Chinese and German vehicles under current tariff regimes, using real-world sales data, vehicle characteristics, and policy scenarios. Where possible, it also explores alternative policy tools such as minimum price floors. The work combines causal inference, machine learning, and agent-based simulation.

Your tasks

• literature review on EV policy, tariff regimes, and automotive market dynamics
• econometric analysis using real-world vehicle registration data and causal inference methods
• exploratory feature analysis using machine learning (e.g., model clustering, competitiveness profiling)
• usage of a utility maximization agent-based model to explore future EV adoption pathways

Your profile

• ongoing studies in Economics, Engineering, Data Science, Systems Modeling, or related fields
• basic knowledge of programming, especially for data analysis and transportation model simulations
• programming experience in Python or R
• experience with data handling and processing, particularly using structured formats such as CSV or similar
• familiarity with machine learning tools (e.g., scikit-learn, pandas, XGBoost)
• interest in electric mobility, international trade, and automotive market dynamics
• independent and structured working style

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 2383) please contact:

Gabriel Möring Martínez