Internship Openings

5 / 53 Intern positions were found.

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 Group E:1 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).

Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer.


  • DA1024: Micro Grid Synchronization and Control

    • Mitsubishi Electric Research Laboratories (MERL) at Cambridge MA is looking for a highly motivated intern to conduct research on Micro Grid Synchronization and Control. The ideal candidate would be a senior Ph.D. student, or postdoctoral researcher, and have solid background in power electronics, generator/grid synchronization, power system control, and energy storage systems. The candidates should have strong programming skills in Matlab or C/C++. The duration of the internship is expected to be 3-6 months, and the start date is flexible.

    • Research Area: Data Analytics
    • Host: Hongbo Sun
    • Apply Now
  • DA1065: Time Series Analytics Intern in Data Analytics

    • The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2017. The ideal candidate is expected to have a strong background in time series analytics with experience in subsequence matching, feature representation, and matching distance development. Preferred candidates will have a background in subsequence matching across multiple time series. The candidate is expected to have strong programming skills in a programming language like C, and a scripting language like Python or Matlab. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Area: Data Analytics
    • Host: Emil Laftchiev
    • Apply Now
  • DA1070: Load Forecasting

    • MERL is looking for a highly motivated individual to work on short-term electric power load forecasting. Successful candidates will collaborate with MERL researchers to derive and implement new algorithms. The ideal candidate is a senior Ph.D. student in electrical and computer engineering or computer science with experience in the following areas: machine learning, optimization algorithms, time series analysis. Capability of implementing the developed algorithms in Matlab or R is expected. The duration of the internship is 3 months. The preferred start date is March 1, 2017.

    • Research Area: Data Analytics
    • Host: Daniel Nikovski
    • Apply Now
  • DA1061: Numerical Methods for Process Applications

    • MERL is seeking a motivated graduate student intern to develop numerical methods for function approximation and regression analysis for target applications that include the representation of thermophysical properties for process applications. The ideal candidate would have a solid background in numerical methods, such as the construction of splines to approximate multivariable functions. Strong programming skills and experience with Python/C/C++/Matlab are expected. Knowledge of Modelica or other equation-oriented languages (gPROMS, Aspen HYSYS), thermodynamics, and/or nonlinear dynamics and control methods is a plus. The expected duration of this internship is 3 months. Please contact Chris Laughman (laughman at merl.com) or go to www.merl.com/internship/ for more information.

    • Research Area: Data Analytics
    • Host: Chris Laughman
    • Apply Now
  • DA1026: Transfer Learning Intern in Data Analytics

    • The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2017. The ideal candidate is expected to have a strong background in machine learning with experience in transfer learning. Preferred candidates will have a background in semi-supervised or unsupervised learning. The candidate is expected to have strong programming skills in Python with experience using pandas, scikit-learn and scipy. Prior experience in Matlab is expected. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Area: Data Analytics
    • Host: Emil Laftchiev
    • Apply Now