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.


  • CI0082: Internship - Quantum AI

    • MERL is excited to announce an internship opportunity in the field of Quantum Machine Learning (QML) and Quantum AI (QAI). We are seeking a highly motivated and talented individual to join our research team. This is an exciting opportunity to make a real impact in the field of quantum computing and AI, with the aim of publishing at leading research venues.

      Responsibilities:

      • Conduct cutting-edge research in quantum machine learning.
      • Collaborate with a team of experts in quantum computing, deep learning, and signal processing.
      • Develop and implement algorithms using PyTorch and PennyLane.
      • Publish research results at leading research venues.

      Qualifications:

      • Currently pursuing a PhD or a post-graduate researcher in a relevant field.
      • Strong background and solid publication records in quantum computing, deep learning, and signal processing.
      • Proficient programming skills in PyTorch and PennyLane are highly desirable.

      What We Offer:

      • An opportunity to work on groundbreaking research in a leading research lab.
      • Collaboration with a team of experienced researchers.
      • A stimulating and supportive work environment.

      If you are passionate about quantum machine learning and meet the above qualifications, we encourage you to apply. Please submit your resume and a brief cover letter detailing your research experience and interests. Join us at MERL and contribute to the future of quantum machine learning!

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing, Applied Physics
    • Host: Toshi Koike-Akino
    • Apply Now

  • EA0070: Internship - Multi-modal sensor fusion

    • MERL is looking for a self-motivated intern to work on multi-modal sensor fusion for health condition monitoring and predictive maintenance of motor drive systems. The ideal candidate would be a Ph.D. candidate in electrical engineering or computer science with solid research background in signal processing and machine learning. Experience in motor drive system is a plus. The intern is expected to collaborate with MERL researchers to collect data, explore multi-modal data relationship, and prepare manuscripts for publications. The total duration is anticipated to be 3 months and the start date is flexible.

      Required Specific Experience

      • Experience with multi-modal sensor fusion.

    • Research Areas: Data Analytics, Electric Systems, Machine Learning, Signal Processing, Artificial Intelligence
    • Host: Dehong Liu
    • Apply Now

  • ST0116: Internship - 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, pose estimation, segmentation, multiple object tracking (MOT), and representation learning on radar data is required. Previous hands-on experience with open indoor and outdoor radar datasets is a plus. Familiarity with basic radar concepts and MERL's recent work in radar perception is an asset. The intern will work closely with MERL researchers to develop novel algorithms, design experiments with MERL in-house testbed, and prepare results for patents and publication. The internship is expected to last 3 months with a preferred start date after June 2025.

      Required Specific Experience

      • Solid understanding of state-of-the-art perception frameworks including transformer-based (e.g., DETR) and diffusion-based (e.g., DiffusionDet) methods.
      • Hands-on experience with open large-scale radar datasets such as MMVR, HIBER, RADIATE, and K-Radar.
      • Proficiency in Python and experience with job scheduling on GPU clusters using tools like Slurm.
      • Proven publication records in top-tier venues such as CVPR, ICCV, ECCV, NeurIPS.
      • Knowledge of basic radar concepts such as FMCW, MIMO, (micro-) Doppler signature, radar point clouds, heatmaps, and raw ADC waveforms.
      • Familiarity with MERL's recent radar perception research such as TempoRadar, SIRA, MMVR, and RETR.

    • Research Areas: Computational Sensing, Signal Processing
    • Host: Perry Wang
    • Apply Now

  • ST0096: Internship - Multimodal Tracking and Imaging

    • MERL is seeking a motivated intern to assist in developing hardware and algorithms for multimodal imaging applications. The project involves integration of radar, camera, and depth sensors in a variety of sensing scenarios. The ideal candidate should have experience with FMCW radar and/or depth sensing, and be fluent in Python and scripting methods. Familiarity with optical tracking of humans and experience with hardware prototyping is desired. Good knowledge of computational imaging and/or radar imaging methods is a plus.

      Required Specific Experience

      • Experience with Python and Python Deep Learning Frameworks.
      • Experience with FMCW radar and/or Depth Sensors.

    • Research Areas: Computer Vision, Machine Learning, Signal Processing, Computational Sensing
    • Host: Petros Boufounos
    • Apply Now