Internship Openings

4 / 22 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.


  • 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.

    • Research Areas: Optimization, Machine Learning, Control, Multi-Physical Modeling
    • Host: Chris Laughman
    • Apply Now
  • CV0063: Internship - Visual Simultaneous Localization and Mapping

    • MERL is looking for a self-motivated graduate student to work on Visual Simultaneous Localization and Mapping (V-SLAM). Based on the candidate’s interests, the intern can work on a variety of topics such as (but not limited to): camera pose estimation, feature detection and matching, visual-LiDAR data fusion, pose-graph optimization, loop closure detection, and image-based camera relocalization. The ideal candidate would be a PhD student with a strong background in 3D computer vision and good programming skills in C/C++ and/or Python. The candidate must have published at least one paper in a top-tier computer vision, machine learning, or robotics venue, such as CVPR, ECCV, ICCV, NeurIPS, ICRA, or IROS. The intern will collaborate with MERL researchers to derive and implement new algorithms for V-SLAM, conduct experiments, and report findings. A submission to a top-tier conference is expected. The duration of the internship and start date are flexible.

      Required Specific Experience

      • Experience with 3D Computer Vision and Simultaneous Localization & Mapping.

    • Research Areas: Computer Vision, Robotics, Control
    • Host: Pedro Miraldo
    • Apply Now
  • CA0148: Internship - Motion Planning and Control for Autonomous Articulated Vehicles

    • MERL is seeking an outstanding intern to collaborate in the development of motion planning and control for autonomous articulated vehicles. The ideal candidate is expected to be working towards a PhD in electrical, mechanical, aerospace engineering, robotics, control or related areas, with a strong emphasis on motion planning and control, possibly with applications to ground vehicles, to have experience in at least some of path/motion planning algorithms (A*, D*, graph-search) and optimization-based control (e.g., model predictive control), to have excellent coding skills in MATLAB/Simulink and a strong publication record. The expected start date is the Spring/Early Summer 2025 and the expected duration is 6-9 months, depending on candidate availability and interests.

      Required Specific Experience

      • Path/motion planning algorithms (A*, D*, graph-search)
      • Nonlinear model predictive control
      • Programming in Matlab/Simulink
      • Applications to mobile robots or vehicles

      Additional Useful Experience

      • Nonlinear MPC Design in CasADi
      • Code generation tools and dSPACE
      • Applications to autonomous vehicles and articulated vehicles

    • Research Areas: Control, Dynamical Systems, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CA0129: Internship - LLM-guided Active SLAM for Mobile Robots

    • MERL is seeking interns passionate about robotics to contribute to the development of an Active Simultaneous Localization and Mapping (Active SLAM) framework guided by Large Language Models (LLM). The core objective is to achieve autonomous behavior for mobile robots. The methods will be implemented and evaluated in high performance simulators and (time-permitting) in actual robotic platforms, such as legged and wheeled robots. The expectation at the end of the internship is a publication at a top-tier robotic or computer vision conference and/or journal.

      The internship has a flexible start date (Spring/Summer 2025), with a duration of 3-6 months depending on agreed scope and intermediate progress.

      Required Specific Experience

      • Current/Past Enrollment in a PhD Program in Computer Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, or related field
      • Experience with employing and fine-tuning LLM and/or Visual Language Models (VLM) for high-level context-aware planning and navigation
      • 2+ years experience with 3D computer vision (e.g., point cloud, voxels, camera pose estimation) and mapping, filter-based methods (e.g., EKF), and in at least some of: motion planning algorithms, factor graphs, control, and optimization
      • Excellent programming skills in Python and/or C/C++, with prior knowledge in ROS2 and high-fidelity simulators such as Gazebo, Isaac Lab, and/or Mujoco

      Additional Desired Experience

      • Prior experience with implementation and/or development of SLAM algorithms on robotic hardware, including acquisition, processing, and fusion of multimodal sensor data such as proprioceptive and exteroceptive sensors

    • Research Areas: Artificial Intelligence, Computer Vision, Control, Machine Learning, Optimization, Robotics
    • Host: Alexander Schperberg
    • Apply Now