EA0234: Internship - Multi-modal sensor fusion for predictive maintenance
About The Position
Mitsubishi Electric Research Laboratories (MERL) is seeking a self-motivated Ph.D. candidate in Computer Science, Electrical Engineering, or a related field for a 3-month internship focused on developing advanced machine learning algorithms to fuse multi-modal time sequence data for electric machine condition monitoring and predictive maintenance. The ideal candidate will have a strong background in machine learning and signal processing with a proven publication record. Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL researchers to design and develop novel algorithms, prepare technical reports, and contribute to manuscripts for top-tier scientific publications. This position requires onsite work at MERL, with a flexible start date.
Requirements
- Experience with multi-modal sensor fusion.
- Ph.D. candidate in Computer Science, Electrical Engineering, or a related field
- strong background in machine learning and signal processing with a proven publication record
Nice To Haves
- Experience in time-sequence analysis
- Experience in physics-informed machine learning
- Knowledge of electric machines
Responsibilities
- design and develop novel algorithms
- prepare technical reports
- contribute to manuscripts for top-tier scientific publications
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
