Internship Openings

5 / 13 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.


  • ST2083: Deep Learning for Radar Perception

    • The Computation Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research in radar perception. Expertise in deep learning-based object detection, multiple object tracking, data association, and representation learning (detection points, heatmaps, and raw radar waveforms) is required. Previous hands-on experience on open indoor/outdoor radar datasets is a plus. Familiarity with the concept of FMCW, MIMO, and range-Doppler-angle spectrum is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with MERL in-house testbed, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.

    • Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Dynamical Systems, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • CA2213: Mobile robotics: Sensing, Planning, and Control

    • MERL is seeking a highly motivated intern to collaborate in the development and experimental validation of sensing, planning, and control methods in various robotic testbeds (quadrotors, turtlebots, and mini-cars) at MERL. The ideal candidate is enrolled in a Masters/PhD program in Electrical, Mechanical, Aerospace Engineering, Robotics, Computer Science or related program, with prior experience in some or all of the following: motion planning, control, optimization, learning, computer vision, and their application in mobile robots, including experimental validation. The successful candidate is proficient in ROS2, C/C++, and Python, and at least familiar with MATLAB. The expected duration of the internship is 4-6 months with a flexible start date in the late Fall/Winter 2024.

    • Research Areas: Artificial Intelligence, Control, Robotics
    • Position ID: CA2213
    • Contact: Abraham Vinod
    • Email: vinod[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • OR2103: Human Robot Collaboration in Assembly Tasks

    • MERL is looking for a self-motivated and qualified candidate to work on human-robot-interaction for manipulation and assembly collaborative scenarios. The ideal candidate is a PhD student and should have experience and records in one or multiple of the following areas. 1) Control, estimation and perception for Robotic manipulation 2) Task and Motion Planning 3) Learning from demonstration algorithms applied to robotic manipulation 4) Machine learning techniques for modeling and control as well as regression and classification problems. 5) Experience in working with robotic systems and familiarity with physics engine simulators like Mujoco, Isaac Gym, PyBullet. The successful candidate will be expected to develop, in collaboration with MERL employees, state of the art algorithms to solve complex manipulation tasks that involve human and robot collaborations. Proficiency in Python and ROS are required. The expectation is that the research will lead to one or more scientific publications. The expected duration s 3-4 months, with a flexible starting date.

    • Research Areas: Artificial Intelligence, Machine Learning, Robotics
    • Host: Diego Romeres
    • Apply Now
  • OR2196: Visuo-tactile Learning for Dexterous Manipulation

    • MERL is looking for a highly motivated individual to work on robotic manipulation using visuo-tactile learning. The research will develop robot motor skills for complex, dexterous manipulation using vision and tactile perception. The ideal candidate should have experience in either one or multiple of the following topics: manipulation, tactile sensing, Reinforcement Learning, sim-to-real techniques for manipulation, and grasping. Senior PhD students in robotics and engineering with a focus on contact-rich manipulation are encouraged to apply. Prior experience working with physical robotic systems (and vision and tactile sensors) is required as results need to be implemented on a physical hardware. Good coding skills in Python ML libraries like PyTorch etc. is required. A successful internship will result in submission of results to a peer-reviewed robotics journal in collaboration with MERL researchers. The expected duration of internship is 4-5 months with start date in Aug/Sept 2024. This internship is preferred to be onsite at MERL.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    • Host: Devesh Jha
    • Apply Now
  • CI2091: Robust AI for Operational Technology Security

    • MERL is seeking a highly motivated and qualified intern to work on operational technology security. The ideal candidate would have significant research experience in cybersecurity for operational technology, anomaly detection, robust machine learning, and defenses against adversarial examples. A mature understanding of modern machine learning methods, proficiency with Python, and familiarity with deep learning frameworks are expected. Candidates at or beyond the middle of their Ph.D. program are encouraged to apply. The expected duration is 3 months with flexible start dates.

    • Research Areas: Artificial Intelligence, Machine Learning
    • Host: Ye Wang
    • Apply Now