Internship Openings

8 / 52 Intern positions were found.

Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Group E:1 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).

Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer.


  • MM1009: Audio Analysis

    • We are seeking graduate students interested in working on cutting-edge noise-robust audio analysis and pattern recognition technology for applications in robotics. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for publication. The ideal candidate would be a senior Ph.D. student with experience in audio signal processing, speech modeling, probabilistic modeling and deep learning. The duration of the internship is expected to be 3-6 months. Positions are currently available through Summer 2017. Extra consideration will be given to candidates with availability between now and April 2017.

    • Research Area: Multimedia
    • Host: John Hershey
    • Apply Now
  • MM1007: Source separation

    • We are seeking graduate students interested in helping advance the field of source-separation, speech enhancement in extreme environments, and audio reconstruction (inpainting, bandwidth extension, synthesis), using the latest developments in deep learning. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for publication. The ideal candidate would be a senior Ph.D. student with experience in audio signal processing, speech modeling, probabilistic modeling and deep learning. The duration of the internship is expected to be 3-6 months. Positions are currently available through Summer 2017. Extra consideration will be given to candidates with availability between now and April 2017.

    • Research Area: Multimedia
    • Host: Jonathan Le Roux
    • Apply Now
  • MM1017: Multimodal Active Sensing

    • MERL is looking for a highly-motivated intern to work at the intersection of optical depth sensing and radar. The successful candidate will have expertise in computer vision, optical depth sensing and 3D tracking, and/or radar array signal processing. Familiarity with other active sensing methods and modern signal processing techniques, such as compressive sensing and sparse optimization, are a plus. The expected duration of the internship is 3 months with a possibility of extension, and the start date is flexible. Extra consideration will be given to candidates that are immediately available.

    • Research Area: Multimedia
    • Host: Petros Boufounos
    • Apply Now
  • MM1046: End-to-end acoustic analysis recognition and inference

    • MERL is looking for an intern to work on fundamental research in the area of end-to-end acoustic analysis, recognition, and inference using machine learning techniques such as deep learning and/or Bayesian approaches. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for high impact publication. The ideal candidate would be a senior Ph.D. student with experience in source separation, speech recognition, and/or natural language processing including practical machine learning algorithms with related programming skills. The duration of the internship is expected to be 3-6 months. Positions are available throughout 2017.

    • Research Area: Multimedia
    • Host: Shinji Watanabe
    • Apply Now
  • MM1008: Multi-spectral image fusion

    • MERL is looking for a self-motivated intern to work on multi-spectral image fusion. The ideal candidate would be a senior Ph.D. student with solid background in computer vision, image enhancement and image segmentation. Experience in sparse modeling is desirable. Proficiency in MATLAB and C/C++ programming is necessary. The intern is expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible, expected duration is 3 months.

    • Research Area: Multimedia
    • Host: Dehong Liu
    • Apply Now
  • MM1012: Point Cloud Compression

    • MERL is seeking an intern to work on new methods for coding and compressing 3D point clouds. The ideal candidate will have relevant expertise in computer graphics representation and compression, lossy or lossless image/video compression, familiarity with point cloud data related to mobile mapping and laser scanning, as well as experience with existing compression standards such as HEVC or H.264/AVC. Candidates at or beyond the middle of a Ph.D. program are encouraged to apply.

    • Research Area: Multimedia
    • Host: Bob Cohen
    • Apply Now
  • MM1010: Fluid Dynamics Estimation and Control

    • MERL is seeking a motivated and qualified individual to conduct research in fluid dynamics estimation and control. The ideal candidate should have solid background in PDE model reduction, observability analysis and state observers design for dynamical systems. Familiarity with operator-based model reduction or adaptive control techniques is a plus. Publication of the results produced during the internship is anticipated.

    • Research Area: Multimedia
    • Host: Mouhacine Benosman
    • Apply Now
  • MM1048: Deep Learning for Artificial Intelligence

    • We are seeking graduate students excited about new possibilities in artificial intelligence, driven by the latest advances in deep learning. The research focuses on integrating natural language understanding with multi-modal scene understanding using multi-task learning. The ultimate goal interactive question answering about an observed audio/visual scene, as a step toward developing grounded semantic representations. The ideal candidate would be a senior Ph.D. student with availability for a 3-6 month internship and experience in one or more of natural language, speech, and computer vision. The candidate should be well-versed in deep learning methods for sequential and structured prediction problems, such as attention models, and related programming skills for large scale problems. The internship work is expected to contribute to publications in the field and may serve as a component of the candidate's graduate thesis.

    • Research Area: Multimedia
    • Host: John Hershey
    • Apply Now