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Das Deutsche Zentrum für Luft- und Raumfahrt sucht eine Masterarbeit zu Brennstoffzellenalterung mittels Machine Learning. Ihre Aufgaben umfassen Forschung, Datenanalyse und die Entwicklung eines Modells zur Effizienzsteigerung in Schienenanwendungen. Join our mission for sustainable energy solutions!
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