Master thesis - Development of a Fuel Cell Aging Model using Machine Learning Algorithms (f / m[...]

Deutsches Zentrum für Luft- und Raumfahrt (DLR); Stuttgart; Vor Ort; EUR 45.000 - 55.000; Vollzeit

Zusammenfassung

The German Aerospace Centre (DLR) seeks a Master's thesis candidate for research in fuel cell aging modeling. The role involves data-driven methodologies to enhance energy efficiency in railway applications, offering a chance to work on sustainable technologies within a prestigious research institution.

Leistungen

Training and development opportunities

Diversity and equality initiatives

Qualifikationen

• Interest in sustainable energy systems and fuel cell technologies.
• Independent and proactive way of working.

Aufgaben

• Conduct literature research on PEM Fuel Cells and their application in rail vehicles.
• Implement machine learning algorithms to estimate fuel cell aging using Python.
• Evaluate model performance and propose strategies to improve efficiency.

Kenntnisse

Machine learning algorithms

Energy systems

Python programming

Written and spoken English skills

Ausbildung

Ongoing studies in Computer Science, Data Engineering, Mechanical Engineering, Vehicle Engineering, Energy Engineering, Aerospace Engineering

Jobbeschreibung

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

We are looking for a Master’s thesis candidate to investigate fuel cell aging modeling methods as part of our efforts to improve energy efficiency and enhance the sustainability of rail operations. Your focus will be on using data-driven and machine learning approaches to develop a fuel cell aging model, as well as identifying strategies to increase the fuel cell lifespan and overall efficiency in railway applications.

• Literature research on PEM Fuel Cells and their application in rail vehicles.
• Literature research on Fuel cell aging modelling methods.
• Select and implement suitable machine learning algorithms to estimate fuel cell aging, using available data and specific requirements, in Python
• Evaluate the model's performance and propose strategies to improve fuel cell lifespan and improve overall efficiency.

Your profile

• Ongoing academic studies in Computer science, Data engineering, Mechanical Engineering, Vehicle Engineering, Energy Engineering, Aerospace Engineering, or related fields in the natural and engineering sciences.
• Interest in sustainable energy systems, fuel cell technologies, and the application of machine learning in energy management.
• Knowledge in energy systems, machine learning algorithms and python programming
• Good written and spoken English skills
• Independent and proactive way of working

Depending on qualifications and assignment of tasks up to pay group E05 TVöD.

We look forward to getting to know you!

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

If you have any questions about this position (Vacancy-ID 1148) please contact :