Internship Openings

9 / 41 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.

Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.

In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting. Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered "at-will," and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.


  • CI0197: Internship - Embodied AI & Humanoid Robotics

    • Those who are passionate about pushing the boundaries of embodied AI, join our cutting-edge research team as an intern and contribute to the development of generalist AI agents for humanoid robots. This is a unique opportunity to work on impactful projects aimed at publishing in top-tier AI and robotics venues.

      What We’re Looking For

      We’re seeking highly motivated individuals with:

      • Advanced research experience in robotic AI, edge AI, and agentic AI systems.
      • Hands-on expertise in Vision-Language-Action (VLA) models and Foundation Models
      • Strong proficiency with Python, PyTorch/JAX, deep learning, and robotic agent frameworks

      Internship Details

      • Duration: ~3 months
      • Start Date: Flexible
      • Goal: Publish research at leading AI/robotics conferences and journals

      If you're excited about shaping the future of humanoid robotics and AI agents, we’d love to hear from you!

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Applied Physics, Artificial Intelligence, Computer Vision, Control, Machine Learning, Robotics, Signal Processing, Speech & Audio, Optimization
    • Host: Toshi Koike-Akino
    • Apply Now

  • CI0190: Internship-IoT Network Methodology

    • MERL is seeking a highly motivated and qualified intern to carry out research on UAV assisted IoT network methodology. The candidate is expected to develop innovative path planning technologies to support UAV swarm navigation in IoT network environments. The candidates should have knowledge of communication network technologies such as path planning and cooperative network operations. Knowledge of control technology and path management is a plus. Start date for this internship is flexible and the duration is about 3 months.

      Responsibilities for this position include:

      • Research on UAV assisted IoT networks
      • Develop path planning technologies to support UAV coordination in IoT networks
      • Simulate and analyze the performance of developed technology

      Qualifications for this position are:

      • Junior and senior year Ph.D students

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Communications, Control, Dynamical Systems, Machine Learning, Optimization, Robotics, Signal Processing
    • Host: Jianlin Guo
    • Apply Now

  • EA0228: Internship - Constraint Modeling and Optimal Control

    • MERL is seeking a highly motivated and qualified individual to conduct research in differentiable constraint modeling and optimal control of high performance motion systems. The ideal candidate should have solid backgrounds in sensitivity analysis, reachability analysis, and optimal control. A proven record of publishing results in leading conferences/journals is necessary. Demonstrated experience of using dSPACE for real-time HIL experimentation is a plus. Ph.D. students in electrical engineering, control, and related areas are encouraged to apply. Start date for this internship is around summer 2026 and the duration is about 3 months.

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Yebin Wang
    • Apply Now

  • EA0226: Internship - Sample Efficient Safe Reinforcement Learning

    • MERL is seeking a highly motivated and qualified individual to conduct research in the sample efficient safe reinforcement learning via the integration of model- and learning-based theories, with applications to ultra-high precision positioning systems. The ideal candidate should have solid backgrounds in dynamical systems, control theory and reinforcement learning, and strong coding skills. Prior experience on ultra-high precision motion control systems is a plus. Ph.D. students in learning and control are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Machine Learning, Control, Optimization
    • Host: Yebin Wang
    • Apply Now

  • EA0235: Internship - Planning and Control of Mobile Manipulators

    • MERL is seeking a highly motivated and qualified individual to conduct research on fast/robust whole-body motion planning and control of mobile manipulators for agility, safety and precision. The ideal candidate should demonstrate solid background and track record of publications in the areas of robotic dynamics, motion planning, and control. Strong C++ and Python coding skills, knowledge of robotic software such as Pinocchio/Pybullet/MuJoCo, and optimization tools such as CasADi/PyTorch are a necessity. Ph.D. students in mechanical engineering, robotics, computer science, and electrical engineering are encouraged to apply. Start date for this internship is around summer 2026 and the duration is about 3 months.

      Required Specific Experience

      • Experience with robotic software such as Pinocchio/Pybullet/MuJoCo/ROS
      • Strong C++ and Python coding skills
      • Optimization tools such as CasADi/PyTorch

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Control, Robotics, Optimization, Machine Learning
    • Host: Yebin Wang
    • Apply Now

  • MS0098: Internship - Control and Estimation for Large-Scale Thermofluid Systems

    • MERL is seeking a motivated graduate student to research methods for state and parameter estimation and optimization of large-scale systems for process applications. Representative applications include large vapor-compression cycles and other multiphysical systems for energy conversion that couple thermodynamic, fluid, and electrical domains. The ideal candidate would have a solid background in control and estimation, numerical methods, and optimization; strong programming skills and experience with Julia/Python/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics, or equation-oriented languages (Modelica, gPROMS) is a plus. The expected duration of this internship is 3 months.

      The pay range for this internship position will be 6-8K per month.

    • Research Areas: Optimization, Machine Learning, Control, Multi-Physical Modeling
    • Host: Chris Laughman
    • Apply Now

  • CA0153: Internship - High-Fidelity Visualization and Simulation for Space Applications

    • MERL is seeking a highly motivated graduate student to develop high-fidelity full-stack GNC simulators for space applications. The ideal candidate has strong experience with rendering engines, synthetic image generation, and computer vision, as well as familiarity with spacecraft dynamics, motion planning, and state estimation. The developed software should allow for closed-loop execution with the synthetic imagery, and ideally allow for real-time visualization. Publication of results produced during the internship is desired. The expected duration of the internship is 3-6 months with a flexible start date.

      Required Specific Experience

      • Current enrollment in a graduate program in Aerospace, Computer Science, Robotics, Mechanical, Electrical Engineering, or a related field

      • Experience with one or more of Blender, Unreal, Unity, along with their APIs

      • Strong programming skills in one or more of Matlab, Python, and/or C/C++

      The pay range for this internship position will be6-8K per month.

    • Research Areas: Computer Vision, Control, Dynamical Systems, Optimization
    • Host: Avishai Weiss
    • Apply Now

  • CA0178: Internship - Planning and Control of Multi-robot systems

    • MERL is seeking a highly motivated intern to collaborate in the development decision making, planning and control for teams of ground robot in task such as coverage control, monitoring and pursuit-evasion. The ideal candidate is a PhD student with strong experience in planning and control of multi-agent systems, with background in advanced model-based (e.g., MPC) and learning-based (e.g., RL) methods. The results of the internship are expected to be published in top-tier conferences and/or journals. The internship will take place during Fall/Winter 2025 (exact dates are flexible) with an expected duration of 3-6 months.

      Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, etc., indicating your proficiency.

      Required Experience

      • Current enrollment in a PhD program in Mechanical, Electrical, Aerospace Engineering, Computer Science or related programs, with a focus on Robotics and/or Control Systems
      • Experience in as many as possible of:
        • Formal methods and set based methods (temporal logics, reachability, invariance)
        • Model predictive control (design, analysis, solvers)
        • Reinforcement learning for planning
        • Cooperative planning and control for multi-agent systems
        • Programming in Python or Matlab or Julia

      Additional Useful Experience

      • Knowledge of one or more physics simulators for robotics (e.g., MuJoco)
      • Experience with coverage control and pursuit-evasion problems
      • Programming in C/C++ or Simulink code generation

      The pay range for this internship position will be6-8K per month.

    • Research Areas: Control, Dynamical Systems, Robotics
    • Host: Stefano Di Cairano
    • Apply Now

  • OR0217: Internship - Fast Electromagnetic Transient Analysis of Power Grids

    • Mitsubishi Electric Research Laboratories (MERL) is seeking a highly motivated Ph.D. student intern to conduct research on electromagnetic transient analysis of power grids. The ideal candidate will have a strong background in power systems, transient analysis, dynamic simulation, converter control, numerical methods, and optimization. Proficiency in MATLAB, Python, or C++ is required. Prior experience with electromagnetic transient analysis will be considered a plus. This internship is expected to last three to six months, with a flexible start date. The pay range for this internship position will be 6-8K per month.

    • Research Areas: Control, Data Analytics, Dynamical Systems, Electric Systems, Optimization
    • Host: Hongbo Sun
    • Apply Now