The role focuses on improving battery charging performance, safety, and efficiency through data-driven modeling and control strategies
Job Summary
The role focuses on improving battery charging performance, safety, and efficiency through data-driven modeling and control strategies.
Candidates will develop physics-based data-driven models for lithium-ion batteries and implement state estimation algorithms for SOC and SOH.
This position contributes to the University's mission of advancing energy technologies and supporting electric mobility through collaborative research.
Matching Summary
Match Score: 75
The role focuses on improving battery charging performance, safety, and efficiency through data-driven modeling and control strategies.
Skills & Requirements
Must-have
Master's degree in Electrical Engineering
Li-ion battery modeling expertise
State estimation algorithm design
Python and MATLAB programming proficiency
Mathematical modeling and data analytics
Nice-to-have
Wireless power transfer optimization experience
Predictive maintenance research background
Battery thermal and health management knowledge
Strong verbal and written communication skills
Experience with LTspice simulation tools
Key Requirements
Master's degree in Electrical Engineering or related fields
Expertise in developing control algorithms
Research experience in predictive maintenance or battery management