The DLR Institute of Technical Thermodynamics, with research facilities in Stuttgart, Ulm, Cologne-Porz, Oldenburg, and Hamburg, employs over 270 people conducting research in the field of efficient and resource-saving energy storage and energy conversion technologies.
What to expect
The Department of Computational Electrochemistry at the Helmholtz Institute Ulm for Electrochemical Energy Storage (HIU) develops new theories and tools for the simulative investigation of battery materials and cells. As part of the excellent battery research in Ulm, we work at the interface between basic research and applied research. In an interdisciplinary team, we investigate the physical-chemical processes in batteries from the nanoscale to the macroscale.
New battery technologies open up a wide range of new applications, particularly in the aerospace industry. The safe operation of the cells is a top priority and requires the most accurate possible determination of the state of charge and health of the cells. In the Microstructure Simulation and Applications group, detailed models are developed to accurately predict the physical-chemical processes in the battery and thus its performance and ageing. Despite the use of supercomputers, these models are too complex to describe the cell behavior in the application in real time.
Therefore, during your PhD project you will use and develop approaches from the field of machine learning to create digital twins of new battery technologies with the help of information from physico-chemical models, sensors and operando measurements. In particular, this approach should make it possible to track the complex physical and chemical processes in lithium-sulfur batteries in real time, predict critical operating conditions and derive countermeasures. The digital twins thus enable the safe operation of the cells in various applications on land, in the air and even in space.
As a member of an internationally leading research team in the field of battery simulation, you will make an important contribution to the understanding and optimization of key technologies. We offer you an attractive research environment to conduct your PhD, room for your own ideas and international visibility.
Your tasks
- development and research on machine learning approaches for digital twins of lithium-sulfur batteries
- training the models using heterogeneous data sets from simulation and experiment
- collaboration on projects to validate and integrate the approaches for various applications at DLR
- presentation of the results at conferences and publication in scientific journals
Your profile
- excellent analytical skills demonstrated by a master’s degree in Engineering, Physics, or Mathematics
- great interest in exploring the possibilities of machine learning
- good knowledge of the theory, modeling and simulation of physical processes
- good programming skills in Python
- passion for innovative research
- proficient English language skills
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 2460) please contact:
Timo Danner
Tel.: +49 711 6862 8218
