Research Fellow (Materials Science and Engineering)

We are looking for a highly talented and motivated candidate to work on Methods to optimize 2nd life battery performance through an AI-assisted battery management system. The project will aim at optimizing the prediction of the remaining useful life of second life batteries based on extended cycling data under varying environmental conditions and post-mortem analysis of the failed cells as the basis for an AI-optimised battery management algorithm. The project will be conducted in cooperation with an industry partner on real full-scale second life batteries. A good understanding of the electrical and electrochemical hazards is required to conduct the project safely. Some of the experiments will have to be conducted at the industry partner’s facility (in Singapore).
The position will be open from now until 31 July 2022.

• PhD in Materials Science, Electrical Engineering or related disciplines is expected
• Several Years of prior knowledge of electrochemical battery characterisation is required.
• Ability to work independently and in interdisciplinary teams is necessary.
• Good writing and presentation skills are needed
• The job requires work in different academic and industrial laboratories in Singapore.

Location: Kent Ridge Campus

Organization: Engineering

Department : Materials Science And Engineering

Employee Referral Eligible: No

Job requisition ID : 7327