Internship Openings

17 / 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.


  • 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
  • ME1049: Model predictive control theory algorithms applications

    • MERL is looking for highly motivated individuals to work on model predictive control theory, algorithms, and applications. Successful candidates will collaborate with MERL researchers to derive and implement new control designs and optimization algorithms, and to analyze and prove their properties. The ideal candidate is a senior Ph.D. student with experience in at least some of the following areas: predictive control, optimization algorithms, modular control design, integration of identification and control, invariance and Lyapunov methods. Publication of relevant results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab is expected; capability of coding parts of the algorithms in C is a plus. The duration of the internship is 3-6 months. Start date is flexible, between February and July 2017.

    • Research Area: Mechatronics
    • Host: Stefano Di Cairano
    • Apply Now
  • ME1021: Nonlinear estimation

    • MERL is seeking a motivated and qualified individual to conduct research in control of electrical machines. The ideal candidate should have solid backgrounds in nonlinear estimation and electrical machines, demonstrated capability to publish results in leading control journals, and experience with Matlab/Simulink and real-time control experiments involving high power devices. Start date for this internship is around May 2017 and the duration is about 3 months.

    • Research Area: Mechatronics
    • Host: Yebin Wang
    • Apply Now
  • ME1041: Exploiting Structure in Optimization and Control

    • MERL is seeking a motivated and qualified individual to conduct research on exploiting structure in control and optimization problems. The ideal candidate should have a solid background in mathematics, optimization, and/or optimal control. PhD students in engineering, operation research, or mathematics with focus on optimization or control are encouraged to apply. The intern will collaborate with MERL researchers in developing algorithms for reducing the computational complexity of optimization and optimal control problems. Start date for this internship is flexible and the expected duration is approximately 3-6 months.

    • Research Area: Mechatronics
    • Host: Claus Danielson
    • 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
  • 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
  • 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
  • ME1066: formal methods for autonomous vehicles

    • MERL is seeking highly motivated individuals to work on formal methods for planning and control of autonomous vehicles. Successful candidates will collaborate with MERL researchers to develop novel control designs and algorithms for vehicle planning and control that achieve safety and liveness properties, and to verify the performance in simulation and possibly in an scaled experimental setup. The ideal candidate is a senior Ph.D. student with experience in at least some of the following areas: formal methods for control, set-based control and invariance, predictive and constrained control, vehicle dynamics. Publication of relevant results in conference proceedings and journals is expected. Capability of algorithm implementation and evaluation in Matlab is expected, capability of coding in C/C++ and executing experiments in a ROS-based robotic environment is desired. The duration of the internship is 3-6 months. Start date is flexible, between February and September 2017.

    • Research Area: Mechatronics
    • Host: Stefano Di Cairano
    • Apply Now
  • ME1028: Predictive Control of Space Vehicles

    • MERL's Mechatronics group is seeking a highly motivated intern for a research position in predictive control of space vehicles. The ideal candidate is working towards a Ph.D. in aerospace, mechanical, or electrical engineering, and has background in both optimization-based control and space vehicle dynamics. The candidate is expected to possess strong abilities in algorithm analysis and Matlab implementation. The duration of the internship is approximately 3 months. Publication of results produced during the internship is expected.

    • Research Area: Mechatronics
    • Host: Avishai Weiss
    • Apply Now
  • ME1059: Atmospheric fluid dynamics modeling and estimation

    • The Mechatronics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2017. The ideal candidate will be a senior Ph.D. student specializing in fluid dynamics, with experience in atmospheric science, turbulence modeling, and computational fluid dynamics (CFD). Research experience in model reduction and data-driven methods is very desirable. Familiarity with computational programming languages like MATLAB, Fortran or C++ is expected. Publication of results obtained during the internship is expected. The starting date is flexible between April-June 2017, and the internship will last 3-4 months.

    • Research Area: Mechatronics
    • Host: Saleh Nabi
    • 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
  • 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
  • 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
  • ME1033: 3D Printing in Extreme Environments

    • MERL's Mechatronics group is seeking a highly motivated intern for a research position on additive manufacturing in extreme environments. The ideal candidate is working towards a Ph.D. in material science, mechanical, or aerospace engineering, and has background in 3D printing and electromagnetics. Experience with CAD and hands-on mechatronics is desired. The expected duration of the internship is approximately 3-6 months. Publication of results produced during the internship is expected.

    • Research Area: Mechatronics
    • Host: Avishai Weiss
    • Apply Now
  • ME1034: Optimal transport and PDE based control

    • MERL is looking for a highly motivated intern to work on developing theory and algorithms for PDE-based control algorithms for nonlinear multi-agent and swarm systems. The ideal candidate would be a senior Ph.D. student working on swarm planning, PDE-based control or mean-field control theory. Exposure to dynamical systems techniques, fluid mechanics and geometric mechanics/geometric control theory is highly desirable. The internship will last 3-4 months, with possibility of an extension. The starting date is flexible. Publication of work done during the internship is expected.

    • Research Area: Mechatronics
    • Host: Piyush Grover
    • Apply Now
  • ME1040: Control of Systems with Constraints

    • MERL is seeking a motivated and qualified individual to conduct research on constrained control problems. The ideal candidate should have a solid background in model predictive control, constrained control, and/or optimization. PhD students in engineering, operation research, or mathematics with focus on control are encouraged to apply. The intern will collaborate with MERL researchers in developing algorithms for controlling systems subject to state and input constraints. Start date for this internship is flexible and the expected duration is approximately 3-6 months.

    • Research Area: Mechatronics
    • Host: Claus Danielson
    • 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