Master's student (f/m/x) - Hybrid PEM Fuel Cell Aging Model Development

What to expect

We are looking for a motivated Master’s student interested in an internship or student assistant position to join our team and support our research on next-generation railway propulsion and energy systems. Our work focuses on developing and analyzing innovative concepts that improve the sustainability, efficiency, and durability of railway propulsion systems using a variety of simulation techniques. As part of the team, you will contribute to improving the understanding of fuel cell aging and support the development of strategies for increasing the lifetime and reliability of fuel cell systems in railway applications.

Your tasks

• Conduct a literature review on PEM fuel cell degradation mechanisms and aging modeling approaches.
• Familiarize yourself with our existing physics informed hybrid PEM fuel cell aging modeling framework.
• Analyze Fuel cell stack measurement data from test vehicle.
• Calibrate and optimize model parameters using experimental measurement data.
• Validate model using measurement data from test vehicle.
• Document and present the methodology and results.

Your profile

• Enrolled in Master’s degree program in computer science, engineering, natural sciences or comparable field of study.
• Strong interest in model-based development and simulation.
• Knowledge in data analysis and machine learning methods.
• Experience with Python coding.
• Good written and spoken English skills.
• Independent, structured and motivated way of working