PhD thesis: Machine Learning Guidance of the Manufacturing Process of Solid Oxide Fuel Cells and Electrolyzers (France/Germany)

This is an opening of a PhD thesis position between Université de Picardie Jules Verne (France), in the team of Prof. Alejandro A. Franco, and the Forschungszentrum Jülich (Germany) in the team of Dr. Olivier Guillon.

This PhD thesis targets the development of a computational methodology to predict and optimize the impact of manufacturing parameters on the architectural and electrochemical properties of solid oxide cells for electrolysis production of hydrogen and fuel cells for electricity generation. This methodology will be based on an original coupling of mechanistic multi-scale modeling with machine learning, and using experimental data from a prototyping line.

We are looking for an individual who is willing to undertake this international and cutting-edge scientific project between the two groups, and having the following skills/qualifications:

- MSc. diploma or equivalent already obtained or to be obtained as the latest in September 2022;

- Excellence in courses (good grades in undergraduate and graduate levels);

- Background in physics or materials science and/or data science, experience with applied mathematics.

- International mobility, excellent level of English;

- Scientific open-mindedness, dynamism, autonomy, critical thinking, team spirit.

Deadline for applications is on May 17, 2022. Interested applicants, please send your CV and transcripts (grades) of the Master level to [email protected]