Master's Thesis: Design of Experiments (DoE) & Modeling of Active Thermography

Identifying relevant process and measurement parameters as well as sources of variation, and quantifying their effects; developing and conducting a statistical design of experiments for active thermography to test contaminated battery electrodes; creating a regression model to predict the detectability of contamination and deriving optimal test parameters.

Master's studies in electrical engineering, mechanical engineering, physics, production engineering, data science, or a similar field; sound knowledge of statistical design of experiments, such as response surface methodology; experience with regression models and data analysis, ideally in Python; independent, structured, and analytical way of working, with initiative in conducting experiments at the test bench.