Master thesis - Development of a Fuel Cell Aging Model using Machine Learning Algorithms (f/m/x) Job Details

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Master thesis - Development of a Fuel Cell Aging Model using Machine Learning Algorithms (f/m/x)

Job Description

Req ID: 1148

Place of work: Stuttgart

Starting date: sofort

Career level: Student research project and final thesis

Type of employment: Part time

Duration of contract: 4-6 Monate

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

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.

Your tasks

Literature research on PEM Fuel Cells and their application in rail vehicles.
Literature research on Fuel cell aging modelling methods.
Analyzing available data.
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 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.

We look forward to getting to know you!

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

Marcel Konrad
Tel.: +49 711 6862 497