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Applications are invited for a funded PhD in the area of Predictive Prognostics for Lithium-ion Battery at INSA Strasbourg funded by HALFBACK and VEHICULE projects.
The proposed thesis aims to mix battery life extension and battery ageing analysis using new techniques of machine learning. Interested readers may refer the attached description for further details about the projects and the phd tasks.
Specific knowledge: Programming skills in machine learning libraries such as tensorflow, keras to cite a few. Also, knowledge in CAN-BUS technology, advanced automatic strategies and multi-physical modeling are very appreciated.
Desired education: Master or Engineer (Bac + 5) with a specialization in Computer Science, Electrical Engineering, or Electronics and Automatics Engineering.
Desired personal skills: High motivation for innovation and the search for operational solutions in an industrial context. Motivation for the combination of simulation and experimentation.
Application process: Applicants interested in this phd can send a detailed CV (curriculum vitae), a motivation letter and the grades of the 3 previous years to Dr. Tedjani Mesbahi (firstname.lastname@example.org) and Dr. Ahmed Samet (email@example.com). Applications will be accepted until the job is filled.