TOPIC #1
A Machine Learning Approach to Electrode Wetting and Formation Cycling in Batteries
Research area: Advanced Methods
Keywords: Lithium-ion batteries; computational modeling, machine learning, robotics, cell manufacturing, electrolyte filling, formation cycling, impedance spectroscopy
Supervising team: Alejandro A. Franco & Corsin Bataglia
Abstract
The Université de Picardie Jules Verne (France) and Empa, the Swiss Federal Laboratories for Materials Science and Technology (Switzerland) invite applications for a joint PhD position focused on optimizing lithium-ion battery manufacturing combining computational modelling, machine learning, robotics, and electrochemical impedance spectroscopy. The project aims to develop a physics-informed surrogate model describing electrolyte filling and formation cycling and validating it experimentally on Empa’s automated robotic platform. The successful candidate will be jointly supervised by Prof. Alejandro A. Franco and Prof. Corsin Battaglia and will gain interdisciplinary training in battery science, computational modelling, machine learning, automation, and advanced materials characterization within the Marie Skłodowska-Curie COFUND programme DESTINY2.
Interest for the student
Expected mobility: The PhD student will be enrolled at the Université de Picardie Jules Verne (UPJV) under the supervision of Prof. A. A. Franco and the co-supervision of Prof. C. Battaglia from Empa (secondment place). During her/his time at Empa, the PhD student has the option to stay at the Empa guest house. (https://www.empa.ch/web/s608/guesthouses, first come, first served). Participation at Destiny events, Swiss Battery Days, selected Alistore and Battery2030+ events, and ECS, MRS, or EMRS conferences during 2nd and 3rd year subject to prior accepted publications in international journals are foreseen. Additional training as needed at Université de Picardie Jules Verne or ETH Zurich.
Career opportunities: The project’s focus on accelerating battery manufacturing processes positions the student for impactful roles in academic and corporate R&D and manufacturing. The student will gain hands-on experience in cutting-edge battery research, combining electrochemical impedance spectroscopy, machine learning, automation, and advanced materials characterization, developing a unique interdisciplinary skill set. The collaboration between Université de Picardie Jules Verne and Empa ensures exposure to an international research environment, fostering a strong scientific network.
Contacts
IMPORTANT: you may contact the potential supervisors to have more information about the topic, however, sending them your application directly is not permitted.
