Internship Openings

4 / 21 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.


  • 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

  • SA0187: Internship - Sound event and anomaly detection

    • We are seeking graduate students interested in helping advance the fields of machine sound source separation, sound event detection/localization, anomaly detection, and physics informed deep learning for machine sounds in extremely noisy conditions. The interns will collaborate with MERL researchers to derive and implement novel algorithms, record data, conduct experiments, integrate audio signals with other sensors (electrical, vision, vibration, etc.), and prepare results for publication. Internships regularly lead to one or more publications in top-tier venues, which can later become part of the intern's doctoral work.

      The ideal candidates are senior Ph.D. students with experience in some of the following: audio signal processing, audio source separation (music, speech, or general sounds), microphone array processing, sound event localization and detection, anomaly detection, and physics informed machine learning.

      Multiple positions are available with flexible start dates (not just Spring/Summer but throughout 2026) and duration (typically 3-6 months).

    • Research Areas: Speech & Audio, Signal Processing, Machine Learning, Artificial Intelligence
    • Host: Gordon Wichern
    • Apply Now

  • SA0186: Internship - Neural Spatial Audio Processing and Understanding

    • We are seeking graduate students interested in advancing the fields of spatial audio, room acoustics, physics informed machine learning, and scene understanding (e.g., sound source localization and spatial-aware captioning). The interns will work closely with MERL researchers to develop novel algorithms, record data, conduct experiments, and prepare results for publication. Internships regularly lead to one or more publications in top-tier venues, which can later become part of the intern's doctoral work. The ideal candidates are senior Ph.D. students with experience in some of the following: microphone array processing, physics informed machine learning, and 3D modeling in computer vision. Multiple positions are available with flexible start date (not just Spring/Summer but throughout 2026) and duration (typically 3-6 months).

    • Research Areas: Speech & Audio, Machine Learning, Signal Processing
    • Host: Yoshiki Masuyama
    • Apply Now

  • EA0183: Internship - machine learning for predictive maintenance

    • Mitsubishi Electric Research Laboratories (MERL) is seeking a self-motivated Ph.D. candidate in Computer Science, Electrical Engineering, or a related field for a 3 month internship focused on developing advanced machine learning algorithms for electric machine condition monitoring and predictive maintenance. The ideal candidate will have a strong background in machine learning and signal processing with a proven publication record, while experience in multi-modal data analysis or domain adaptation is preferred and knowledge of electric machines is a plus. The intern will collaborate with MERL researchers to design and develop novel machine learning algorithms, prepare technical reports, and contribute to manuscripts for top-tier scientific publications. This position requires onsite work at MERL, with a flexible start date.

      Required Specific Experience

      • Experience with Python and Matlab.

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