Internship Openings

8 / 61 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).


  • MP1265: Detecting and localizing nanoparticles

    • MERL is searching for a graduate student to work on properties of nano-particles. Ideal candidates will have a strong background in physics (electromagnetic field) and/or imaging reconstruction algorithms. The applicant should be familiar with programming in Matlab, or Python (Python is preferred). Experience on multi-physics simulation (such as Comsol) is a plus but is not required. The expected duration is 3 months. Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer. Please see our website http://www.merl.com for information relating to our research, and http://www.merl.com/publications/ to explore our publications.

    • Research Areas: Applied Physics, Multi-Physical Modeling
    • Host: Chungwei Lin
    • Apply Now
  • MP1249: Control of Systems with Hybrid Dynamics

    • MERL is seeking an intern to develop optimal control strategies for mode-switching vapor compression systems characterized by discrete changes in dynamics. The ideal candidate has a strong background in hybrid systems, optimization, and event-based control. Proficiency in MATLAB, Python or Julia is required. Senior students enrolled in doctoral programs in engineering, applied mathematics or related fields are encouraged to apply. It is expected that the intern will assist in preparation of results for publication in scientific venues. The duration of the internship is approximately three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • MP1248: Realtime Optimization and Control

    • MERL is seeking an intern to develop realtime optimization strategies to maximize the performance of vapor compression systems. The ideal candidate has a strong theoretical background in extremum seeking, nonlinear and adaptive control, and optimization. Proficiency in MATLAB, Python or Julia is required. Senior graduate students in engineering or mathematics programs at leading research universities are sought. The intern will collaborate with MERL researchers in developing new algorithms, conducting experiments, and preparing manuscripts for scientific publications. The expected duration is roughly three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • MP1262: Thermal modeling for electric motors

    • MERL is looking for a qualified intern to conduct research on thermal modeling and temperature estimation for electric motors. The ideal candidate should have solid background in the physics and engineering of electric machines, in particular the magnetic field calculations, and loss modeling. Related experience on control and estimation theory is a plus. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. Senior PhD students in electrical engineering, mechanical engineering, and other related areas are encouraged to apply. The duration of the internship is about 3 months.

    • Research Areas: Applied Physics, Dynamical 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
  • SP1278: Low Latency Networking

    • MERL is seeking a highly motivated, qualified intern to join the Signal Processing group for a three month internship program. The ideal candidate will be expected to carry out research on low latency networking. The candidate is expected to develop innovative low latency technology in wireless networks. The candidates should have knowledge of low latency networking such as time sensitive networking. Knowledge of wireless network standards such as IEEE 802.11 and simulation tools such as OMNeT++ is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Machine Learning, Multi-Physical Modeling
    • Host: Jianlin Guo
    • Apply Now
  • CD1295: Modeling and data-assimilation of atmospheric flows

  • CD1296: Optimization and Control of Thermo-fluid Systems