At IET-1, we are studying the electrolysis of CO2 for the sustainable conversion of green energy into chemical energy carriers in order to defossilize the chemical industry. The process control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, high-throughput experimental systems will be enhanced using Design of Experiment (DoE) approaches in order to efficiently explore the high-dimensional parameter space of the electrolysis processes. DoE is essential for data-efficient exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and system control interfaces (application programming interface, API) are being developed to automate both process monitoring as well as process control. The API-based integration of the digital twin into the process control of the CO2 electrolysis enables autonomous operation of the system, which can differentiate between market-, system- or network-based operating modes depending on requirements.
Your Project Tasks & Structure:
We work on highly topical, socially relevant issues and offer you the opportunity to actively shape change! You can expect a wide range of opportunities:
In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits
We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.
The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options: https://go.fzj.de/womens-job-journey