Internship Openings

12 / 55 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 and Syria (Country Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).

Rising to the challenges of COVID-19

MERL believes that having an internship be located in MERL's office allows for particularly good interaction between you and those that you will be working with at MERL. In addition, some intern projects, e.g., ones that require specialized laboratory equipment, can only be pursued in our office. We expect that all internships during 2022 will be in-person at MERL.

It is of course possible that COVID will take a significant turn for the worse in 2022. If that happens, we will reevaluate our plans and some internships might have to become remote.

It is a requirement at MERL that everyone working in MERL's space must be fully vaccinated. In order for you to have your internship at MERL, you will have to prove that you are fully vaccinated when you arrive at MERL, ie by showing your vaccination card.


  • CV1703: Software development in ROS for robotic manipulation

    • MERL is offering an internship position for non-research software development for robotic manipulation. The scope of the internship is to develop robust ROS packages by refactoring existing experimental code. The position is open to prospective candidates with very strong programming skills in ROS (Robot Operating System) using C++ primarily and Python respectively. The selected intern will have a software engineering role rather than research oriented. The position is open to both senior undergraduate students and master students. Flexible start and end dates.

    • Research Areas: Computer Vision, Data Analytics, Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1720: Computer Vision for Robotic Manipulation

    • MERL is looking for a highly motivated and qualified intern to work on computer vision for robotic manipulation. The ideal candidate would be a Ph.D. student with a strong background in computer vision, deep learning, and/or robotics. There are several available topics for consideration including task and motion planning (TAMP), learning for object manipulation, and pose estimation. The project requires development of novel algorithms which can be implemented and evaluated on a robotic platform. Experience in working with a physics engine simulator like PyBullet, Mujoco, or Gazebo is preferred. Proficiency in Python programming is necessary and experience with ROS is a plus. Successful candidate will collaborate with MERL researchers and publication of the relevant results is expected. Start date is flexible and expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Siddarth Jain
    • Apply Now
  • CV1738: Robot autonomous grasping using tactile sensing

    • The Computer Vision group is offering an internship opportunity in robot autonomous grasping using tactile sensing. The internship is open to highly skilled graduate students on a PhD track. Candidates should have a solid understanding of reinforcement learning, contact mechanics, simulating contacts, grasping, pose estimation and point cloud processing. The policies will be deployed on physical robots and the sensing is provided by various types of tactile sensing arrays. Strong programming skills are required, including MuJoCo, ROS, C++ and Python. Duration and start dates are flexible.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1721: Deep Learning for Robotic Grasping

    • MERL is looking for a highly motivated and qualified intern to work on computer vision for robotic grasping. The ideal candidate would be a Ph.D. student with a strong background in deep learning and robotics. There are several available topics for consideration including goal-driven grasping of novel objects, grasping for bin picking, and grasping in clutter. The project requires development of novel algorithms which can be implemented and evaluated on a robotic platform. Experience in working with a physics engine simulator like PyBullet, Mujoco, or Gazebo is preferred. Proficiency in Python programming is necessary and experience with ROS is a plus. Successful candidate will collaborate with MERL researchers and publication of the relevant results is expected. Start date is flexible and expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Siddarth Jain
    • Apply Now
  • CV1737: Robotic manipulation using vision and tactile sensing

    • The Computer Vision group at MERL is seeking a highly skilled graduate student for an internship position in Robotic Manipulation using Tactile Sensing and Machine Vision. The research work is expected to be disseminated in a scientific paper and published in one of the major robotics conferences. Candidates should have a solid understanding of contact mechanics, dexterous manipulation and point cloud processing. The intern will deploy the algorithms on physical robots. Strong programming skills are required, including MuJoCo, ROS, C++, Python. Duration and start dates are flexible.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Radu Corcodel
    • Apply Now
  • MD1697: Integrated design of mechatronic systems

    • MERL is seeking a highly motivated and qualified individual to conduct research in model-based mechatronic system design. The ideal candidate should have solid backgrounds in motor and drives, multi-body dynamics, design optimization, and coding skills. Demonstrated experience on hand-on mechatronic system integration, and simulation/optimization software such as Matlab is a necessity. Ph.D. students in mechanical engineering, robotics, and electrical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.

    • Research Areas: Multi-Physical Modeling, Optimization, Robotics
    • Host: Yebin Wang
    • Apply Now
  • SP1718: Brain-Machine Interface

  • DA1768: Contact Modeling and Optimization

    • MERL is looking for a self-motivated and qualified candidate to work on modeling for contact phenomenon. Robotic manipulation is heavily affected by external contacts that can be modeled with physical and data driven models. We are interested in researching those models for analysis and control purposes. The ideal candidate is a PhD student and should have experience and records in multiple of the following areas. Contact modeling and robotic manipulation. Physic Engines like Mujoco, Bullet, Drake and sim2real gap problems. Machine learning techniques for modeling and control such as Gaussian Processes and Neural Networks. Experience in working with robotic systems. Knowledge in learning from demonstration algorithms and standard Reinforcement Learning algorithms is a plus. Proficiency in Python is required. The successful candidate will be expected to develop, in collaboration with MERL employees, state of the art algorithms that will lead to a scientific publication. Typical internship length is 3-4 months.

    • Research Areas: Artificial Intelligence, Dynamical Systems, Machine Learning, Robotics
    • Host: Diego Romeres
    • Apply Now
  • CA1728: Safe data-driven control of dynamical systems under uncertainty

    • MERL is looking for a highly motivated individual to work on safe control of data-driven, uncertain, dynamical systems. The research will develop novel optimization and learning-based control algorithms to guarantee safety and performance in various industrial applications, including autonomous driving. The ideal candidate should have experience in either one or multiple of the following topics: optimal control under uncertainty, (robust and stochastic) model predictive control, (convex and non-convex) optimization, and (reinforcement and statistical) learning. Ph.D. students in engineering or mathematics with a focus on control, optimization, and learning are encouraged to apply. A successful internship will result in submission of relevant results to peer-reviewed conference proceedings and journals, and development of well-documented (Python/MATLAB) code for MERL. The expected duration of the internship is 3-6 months, and the start date is Summer 2022.

    • Research Areas: Artificial Intelligence, Control, Dynamical Systems, Optimization, Robotics
    • Host: Abraham P. Vinod
    • Apply Now
  • CA1731: Motion planning and control of multi-agent systems

    • MERL is looking for a highly motivated individual to develop planning and control algorithms for multi-agent systems. The internship will also include experimental validation of the proposed algorithms in various robotic testbeds (quadrotors and mini-cars) at MERL. The ideal candidate is experienced in multi-agent motion planning and control, and has successfully demonstrated some of their prior work on hardware testbeds. The candidate must be proficient in ROS and C/C++, and at least familiar with Python and MATLAB. Prior experience with crazyflies and/or hamster robots will be considered a plus. The expected duration of the internship is 3-6 months, and the start date is Summer/Fall 2022.

    • Research Areas: Control, Dynamical Systems, Optimization, Robotics
    • Host: Abraham P. Vinod
    • Apply Now
  • CA1742: Mixed-Integer Programming for Motion Planning and Control

    • MERL is looking for a highly motivated individual to work on tailored computational algorithms and applications of mixed-integer programming for decision making, motion planning and control of hybrid systems. The research will involve the study and development of numerical optimization techniques and/or the implementation and validation of algorithms for industrial applications, e.g., related to autonomous driving and robotics. The ideal candidate should have experience in either one or multiple of the following topics: branch-and-bound type methods, heuristics for mixed-integer programming (pre-solve, cutting planes, warm starting, integer-feasible solutions), modeling and formulation of MIPs for hybrid control systems, convex and non-convex optimization, machine learning and real-time optimization. PhD students in engineering or mathematics, especially with a focus on mixed-integer programming or numerical optimization, are encouraged to apply. Publication of relevant results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in MATLAB/Python is expected; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3-6 months and the start date is flexible.

    • Research Areas: Control, Machine Learning, Optimization, Robotics
    • Host: Rien Quirynen
    • Apply Now
  • MS1776: Control for Precise Robotic Assembly

    • MERL seeks a highly motivated intern to perform original research on advanced dynamic control for high-precision robotic assembly. The research will involve developing new model-based algorithms for task planning, path planning, and hybrid nonlinear control of contacts and collisions that occur during assembly operations, specifically using a new type of low mass, programmable impedance direct-drive delta robot with integrated touch sensing. Masters or Ph.D. students with knowledge and expertise in control theory and robotics, and strong working knowledge of C programming and high-level languages such as Julia or Matlab, and with experience and interest in conducting experimental research are encouraged to apply. Publication of results is expected in both leading conferences and journals. The internship is expected to be 3-6 months in duration, preferably in the summer 2022. This internship requires work that can only be done at MERL, so a remote working arrangement will not be considered. This internship requires work that can only be done at MERL.

    • Research Areas: Robotics
    • Host: Scott Bortoff
    • Apply Now