Internship Openings

9 / 30 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 Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).

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


  • ME1060: Networked System Analysis and Design

    • MERL is seeking a motivated and qualified individual to conduct research in analysis, design, and control of large scale networked systems. The ideal candidate should have solid backgrounds in communication channel and network modeling, analysis and design theory for large scale systems, and demonstrated capability to publish results in leading control journals. Experience with manufacturing process is a plus. Start date for this internship is flexible and the duration is about 3 months.

    • Research Area: Mechatronics
    • Host: Yebin Wang
    • Apply Now
  • ME1083: Makerspace Lead Technician

    • Part-time (10 ~ 20 hours/week) Mechatronics Makerspace Lead Technician: Working knowledge of (i) mechanical engineering and of at least one CAD/CAM tool chain, and ability to design a moderately complex mechanical device; (ii) electrical engineering at least one schematic capture / PCB layout tool, and sufficient electronics knowledge to be able to design, implement, assemble, and debug a moderately complex printed circuit. Some ladder work, bending, and lifting less than 50 lbs involved"

    • Research Area: Mechatronics
    • Host: Jay Thornton
    • Apply Now
  • ME1063: Applications of Predictive Control to Mechatronic Systems

    • MERL is seeking a highly motivated individual for collaboration on predictive control theory and its applications. The ideal candidate is expected to have a fundamental understanding of graduate-level control theory with experience in some of the following areas: model predictive control, reference governors, modeling of physical systems and automotive vehicle control. Proficiency in Matlab is expected, and knowledge of C/C++ is a plus. The publication of results in relevant journal and conference proceedings is expected. The duration of the internship will be at least 3 months. Ph.D. candidates in the field of engineering are encouraged to apply.

    • Research Area: Mechatronics
    • Host: Uros Kalabic
    • Apply Now
  • ME1023: Embedded optimization algorithms for realtime control

    • MERL is looking for highly motivated individuals to implement real time optimization algorithms on embedded platforms. The ideal candidate is a MS or Ph.D. student in electrical and computer engineering or computer science with experience developing applications for embedded and real time platforms. Proficiency in C/C++, Matlab, and embedded systems is required. Experience with real time systems is preferred and familiarity with model predictive control or convex optimization algorithms is a plus. The duration of the internship is 3-6 months. Start date is flexible between January and July 2017.

    • Research Area: Mechatronics
    • Host: Dan Burns
    • Apply Now
  • ME1004: Autonomous Vehicle Control

    • MERL is looking for a highly motivated individual to work with MERL researchers on vehicle control, driven by the latest advancements in autonomous vehicles. The ideal candidate has a background in controls with applications to automotive. Knowledge and experience of any of the following techniques is considered a merit: model predictive control, sampling/graph-based motion planning, Bayesian inference. Proficiency in Matlab is expected, and knowledge of C/C++ is a plus. The duration of the internship is 3-6 months. Start date is flexible.

    • Research Area: Mechatronics
    • Host: Karl Berntorp
    • Apply Now
  • ME1005: Deep Learning for Autonomy

    • MERL is seeking a qualified and motivated individual for researching new exciting applications of artificial intelligence and deep learning. The ideal candidate is a senior PhD student with a background in artificial intelligence/deep learning, preferably with experience within automotive and/or robotics. Ph.D. students in computer vision, machine learning, and/or in the intersection of controls and machine learning are encouraged to apply. Proficiency in Matlab and C++ are expected. The expected duration of the internship is 3-6 months and the start date is flexible.

    • Research Area: Mechatronics
    • Host: Karl Berntorp
    • Apply Now
  • ME1029: Experimental Validations of Geometric Control

    • MERL is seeking a highly motivated individual for collaboration on geometric control theory and its applications to vehicle systems. The ideal candidate is expected to have a fundamental understanding of graduate-level control theory with experience in some of the following areas: optimal control, control of nonholonomic systems, numerical optimization, modeling of physical systems, control of automotive or space vehicles. Proficiency in Matlab is expected, and knowledge of C/C++ is a plus. Experience with ROS and Vicon is a plus. The publication of results in relevant journal and conference proceedings is expected. The duration of the internship will be at least 3 months. Ph.D. candidates in the field of engineering are encouraged to apply.

    • Research Area: Mechatronics
    • Host: Uros Kalabic
    • Apply Now
  • ME1069: Path Planning using Invariant Sets

    • The Mechatronics Group at MERL is seeking a qualified and motivated individual for research in path planning algorithms. The ideal candidate has a solid background in control theory, robotics and mathematical analysis, and path-planning algorithms for autonomous systems. Proficiency in MATLAB is necessary. The intern will collaborate with MERL researchers in developing and evaluating algorithms, and preparing results for publication. Ph.D. students in controls, robotics, mechanical engineering, or related areas are encouraged to apply. Start date for this internship is flexible. Expected duration is 3 months.

    • Research Area: Mechatronics
    • Host: Claus Danielson
    • Apply Now
  • ME1022: Advanced MPC technologies

    • MERL is looking for highly motivated individuals to work on developing and implementing high speed optimization algorithms for model predictive control applications. Successful candidates will collaborate with MERL researchers to develop, analyze, and implement optimization algorithms on highly parallel and reconfigurable embedded target hardware. The ideal candidate is a MS or Ph.D. student with experience in model predictive control, optimization algorithms, and GPU and FPGA programming. Proficiency in C/C++ programming, specifically using CUDA and openCL, is required. Experience using openCL to program FPGAs is preferred. Experience with algorithm development in Matlab is preferred. Experience with real time systems is a plus. Publication of relevant results in conference proceedings and journals is expected. The duration of the internship is 3-6 months. Start date is flexible between January and July 2017.

    • Research Area: Mechatronics
    • Host: Bram Goldsmith
    • Apply Now