Internship Openings

2 / 25 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.

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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 and Syria (Country Groups E:1 and E:2 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).

Rising to the challenges of COVID-19

As the COVID-19 pandemic continues to evolve, MERL is committed to providing a safe environment for everyone, during these challenging times.

If you believe you meet the qualifications of one of our open internships, please consider applying for the position of interest. A member of the researcher team will follow up to schedule an interview by phone or video conference for qualified candidates.

Effective on August 20, 2021, MERL will require proof of vaccination for any student who is hired and required to work onsite at MERL, during their internship. Please be sure to check for any specific requirements for onsite work in the job description.


  • DA1687: Unconventional robotic manipulation

    • We are seeking a student interested in robotics, specifically in the areas of tactile sensing, impulse-based (non-prehensile) object manipulation, or other unconventional robotic manipulation, probably with vision assist. The ideal result is a working demo leading to an accepted paper. Applicants should be rising college seniors or graduate students in STEM; prior mechatronics, CAD/CAM, machine vision / machine learning, Python, and open-source development experience is very desirable. The position is immediately available with an expected duration of 3-4 months. This internship requires work that can only be done at MERL.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Bill Yerazunis
    • Apply Now
  • CV1568: Uncertainty Estimation in 3D Face Landmark Tracking

    • We are seeking a highly motivated intern to conduct original research extending MERL's work on uncertainty estimation in face landmark localization (the LUVLi model) to the domains of 3D faces and video sequences. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The candidate should be a PhD student in computer vision and machine learning with a strong publication record. Experience in deep learning-based face landmark estimation, video tracking, and 3D face modeling is preferred. Strong programming skills, experience developing and implementing new models in deep learning platforms such as PyTorch, and broad knowledge of machine learning and deep learning methods are expected.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now