Job Description

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.

Qualifications

• Bachelor Degree in Materials Science, Electrical Engineering or related discipline and several years of relevant research experience is required.
• One Year of prior knowledge of electrochemical battery characterisation is expected.
• 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.

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department : Materials Science And Engineering
Employee Referral Eligible: No
Job requisition ID : 7326