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EA0070: Internship - Multi-modal sensor fusion
MERL is looking for a self-motivated intern to work on multi-modal sensor fusion for health condition monitoring and predictive maintenance of motor drive systems. The ideal candidate would be a Ph.D. candidate in electrical engineering or computer science with solid research background in signal processing and machine learning. Experience in motor drive system is a plus. The intern is expected to collaborate with MERL researchers to collect data, explore multi-modal data relationship, and prepare manuscripts for publications. The total duration is anticipated to be 3 months and the start date is flexible.
Required Specific Experience
- Experience with multi-modal sensor fusion.
- Research Areas: Data Analytics, Electric Systems, Machine Learning, Signal Processing, Artificial Intelligence
- Host: Dehong Liu
- Apply Now
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EA0073: Internship - Fault Detection for Electric Machines
MERL is seeking a motivated and qualified individual to conduct research on electric machine fault analysis and detection methods. Ideal candidates should be Ph.D. students with a solid background and publication record in one more research area on electric machines: electric and magnetic modeling, machine design and prototyping, harmonic analysis, fault detection, and predictive maintenance. Knowledge on data analysis and machine learning algorithms, and strong programming skills using Python/PyTorch are expected. Research experience on modeling and analysis of electric machines and fault diagnosis is desired. Senior Ph.D. students in related expertise, such as electrical engineering, mechanical engineering, and applied physics are encouraged to apply. Start date for this internship is flexible and the duration is 3 months.
- Research Areas: Electric Systems, Machine Learning, Multi-Physical Modeling
- Host: Bingnan Wang
- Apply Now
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EA0069: Internship - PWM inverter switching loss reduction
MERL is looking for a self-motivated intern to work on PWM inverter simulation and design. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in power electronics, control, and optimization. Experience in switching loss reduction modulation is desired. The intern is expected to collaborate with MERL researchers to carry out simulations, optimize design, analyze results, and prepare manuscripts for scientific publications. The total duration is 3 months.
Required Specific Experience
- Experience with simulation tools for PWM inverter design.
- Research Areas: Electric Systems, Signal Processing, Optimization
- Host: Dehong Liu
- Apply Now
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EA0071: Internship - Modeling and Estimation of Electrical Machines
MERL is seeking a highly motivated and qualified individual to conduct research in differentiable modeling, estimation and control of electrical machines. The ideal candidate should have solid backgrounds in dynamical modeling of electrical machines, parameter estimation, and control theory. A proven record of publishing results in leading conferences/journals is necessary. Demonstrated knowledge of sensorless drive and experience of using dSPACE for real-time HIL experimentation is a plus. Senior Ph.D. students in electrical engineering, control, and related areas are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.
- Research Areas: Electric Systems, Control, Dynamical Systems
- Host: Yebin Wang
- Apply Now
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OR0097: Internship - Hybrid AC/DC Power Systems
Mitsubishi Electric Research Laboratories (MERL) in Cambridge, MA, is seeking a highly motivated and qualified individual to join our summer internship program and conduct cutting-edge research on hybrid AC/DC power systems. The ideal candidate should be a senior or junior Ph.D. student in Electrical Engineering or a related field, with in-depth knowledge of AC and DC power systems, renewable generation, power electronics, and power system analysis and control. Strong programming skills in MATLAB, Python, or C/C++ are required. The expected duration of the internship is 3-4 months, and the start date is flexible.
- Research Areas: Electric Systems, Data Analytics
- Host: Hongbo Sun
- Apply Now