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Master Thesis (f/m/x) - Data-driven model development for sulfurized polyacrylonitrile (SPAN)
Job Description
Req ID:  2508
Place of work:  Ulm
Starting date:  01.10.2025
Career level:  Student research project and final thesis, Student employment
Type of employment:  Part time
Duration of contract:  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!

In the department of Computational Electrochemistry, mathematical models of the chemical and physical processes in batteries are developed for an in-depth analysis by means of numerical simulations. The aim is to gain detailed insights into the complex multiscale processes that allow optimization of the battery design with respect to performance and aging.

 

 

What to expect
This master thesis focuses on next-gen lithium-sulfur cells with sulfurized polyacrylonitrile (SPAN) as a novel cathode material. Although these cells have been shown experimentally to have a high potential for aerospace applications, the interaction of chemistry and transport is poorly understood at the model level. However, the latter is essential for an optimal performance.
Therefore, this master thesis aims to develop optimal transport models using data-driven methods. The inverse modeling is realized using the Python solver Firedrake, whereby rate tests and impedance measurements of the cells from experimental project partners are available as a data basis.

 

Your tasks
Following topics should be addressed:

 

  • literature study on data-driven development of transport models
  • selection, implementation and evaluation of suitable approaches
  • development of a methodical workflow that appropriately takes into account the physical information content of different data bases
  • sensitivity analysis with regard to the quality of the input data
  • validation of the optimal set of transport equations
  • documentation of the work

 

The work offers the opportunity to make an important contribution to the further development of lithium-sulfur batteries as a future technology by utilizing synergies between classic methods and modern data-driven approaches.

 

Your profile

  • modelling of transport processes
  • data-driven methods
  • python programming

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 2508) please contact:

 

Timo Danner 
Tel.: +49 711 6862 8218 

 

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