Internship Openings

4 / 40 Intern positions were found.

Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL's employees to perform their job duties may result in discipline up to and including discharge.

Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).


  • DA1387: Disaster-resilient Power Grid

    • MERL is seeking a highly motivated and qualified individual to join our internship program and conduct the research in the area of disaster-resilient power grid. The ideal candidate should have solid background in power systems, mathematical optimization, stochastic analysis, and machine learning. Experience with Matlab or C/C++/Python is required. The duration of the internship is expected to be 3-6 months, and the start date is flexible. Candidates in their senior or junior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Electric Systems
    • Host: Hongbo Sun
    • Apply Now
  • MP1381: Electric Motor Design

    • MERL is seeking a motivated and qualified individual to conduct research in design, modeling, and simulation of electrical machines. The ideal candidate should have solid backgrounds in modeling (including model reduction)/co-simulation of electromagnetics and thermal dynamics of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and real-time control experiments involving motor drives is a strong plus. Senior Ph.D. students in electrical or mechanical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3-6 months.

    • Research Areas: Applied Physics, Electric Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • MP1263: Fault analysis for electric motors

    • MERL is seeking a highly motivated intern to conduct research in electric machine fault analysis. The ideal candidate should be a senior Ph. D student in Electrical Engineering or related discipline with a solid background in the physics and engineering of electric motors, and early fault detection. Knowledge and experience in electric motor modeling and machine learning are desired. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. The duration of internship is expected to be 3 months and start date is flexible.

    • Research Areas: Applied Physics, Electric Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • CD1377: Adaptive Optimal Control of Electrical Machines

    • MERL is seeking a motivated and qualified individual to conduct research in control of electrical machines. The ideal candidate should have solid backgrounds in adaptive dynamic programming and state/parameter estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.

    • Research Areas: Control, Electric Systems, Machine Learning
    • Host: Yebin Wang
    • Apply Now