Internship Openings

8 / 67 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.

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 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

The COVID pandemic has impacted every aspect of life-how we live, work, and interact. At MERL, we are committed to maintaining our internship program through these challenging times.

MERL continues to actively seek candidates for research internships -- some of the posted positions are immediately available, while others target the summer of 2021. Please consider applying for positions of interest. Our researchers will follow up to schedule an interview by phone or video conference for qualified candidates.

Due to the situation with the COVID-19 pandemic, our current internships are mostly remote. Next summer we hope the situation will be better and our internships will be at MERL, but if it is not, most internships will continue to be remote. However, some of the internships require onsite work. Please check for any specific requirements for onsite work in the job description.


  • SP1551: Algorithms for Large-Scale Optimal Transport

    • The Computational Sensing team at MERL is seeking motivated individuals to develop scalable optimal transport algorithms. Ideal candidates should be Ph.D. students with research experience in optimal transport and scalable optimal transport algorithms. Experience with GPU implementations is a plus. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computational Sensing, Computer Vision, Machine Learning, Optimization, Signal Processing
    • Host: Yanting Ma
    • Apply Now
  • SP1543: Technologies for multimodal 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 hardware interfacing, C++, Python, and scripting methods. Experience with radar prototyping hardware is desired but not necessary. Good knowledge of computational imaging and/or radar imaging methods is a plus. This internship requires work that can only be done at MERL.

    • Research Areas: Computational Sensing, Signal Processing
    • Host: Petros Boufounos
    • Apply Now
  • SP1542: Research in Computational Sensing

    • The Computational Sensing team at MERL is seeking motivated and qualified individuals to assist in the development of computational methods for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, sensing of dynamical systems, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computational Sensing, Dynamical Systems, Signal Processing
    • Host: Petros Boufounos
    • Apply Now
  • SP1504: Coherent Imaging Systems

    • MERL is seeking an intern to work on coherent optical imaging. The ideal candidate would be an experienced PhD student or post-graduate researcher working in coherent imaging. The candidate should have a detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR. Strong programming skills in MATLAB are essential. Experience of working in an optical lab environment is a required. Duration is 3 to 6 months. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computational Sensing, Electronic and Photonic Devices
    • Host: David Millar
    • Apply Now
  • SP1585: Three dimensional Imaging from Compton Camera

    • The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that reconstruct a three dimensional distribution of a radioactive source when observed using a Compton camera. The project goal is to improve the performance and develop an uncertainty analysis of these algorithms. Ideal candidates should be Ph.D. students and have solid background and publication record in 3D Compton imaging. Experience in computational tomography, imaging inverse problems, and large-scale optimization is also preferred. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Applied Physics, Computational Sensing, Computer Vision, Machine Learning, Optimization, Signal Processing
    • Host: Hassan Mansour
    • Apply Now
  • SP1510: Learning for inverse problems and dynamical systems

    • The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that solve inverse problems in computational sensing that incorporate deep learning architectures for a variety of sensing applications. The project goal is to improve the performance and develop an analysis of algorithms used for inverse problems by incorporating new tools from machine learning and artificial intelligence. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, large-scale optimization, plug-and-play priors, learning-based modeling for imaging, learning theory for computational imaging, and Koopman theory/dynamic mode decomposition. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
    • Host: Hassan Mansour
    • Apply Now
  • SP1512: Mutual Interference Mitigation

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in mutual interference mitigation for automotive radar. Previous experience in waveform design, radar detection under interference, joint communication and sensing, interference mitigation, and deep learning for radar is highly preferred. Knowledge about automotive radar schemes (MIMO and waveform modulation, e.g., FMCW, PMCW, and OFDM) is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, and prepare results for patents and publication. Senior Ph.D. students with research focuses on signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date.

    • Research Areas: Artificial Intelligence, Communications, Computational Sensing, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • SP1506: Learning-based Wireless Sensing

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in learning-based wireless sensing using communication signals (such as WiFi, Bluetooth, 5G) and other RF signals (such as FMCW). Previous experience in occupancy sensing, people counting, localization, device-free pose/gesture recognition, and skeleton tracking with deep learning is highly preferred. Familiarity with IEEE 802.11 (g/n/ac/ad/ay)standards is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, and prepare results for publication. Senior Ph.D. students with research focuses on wireless communications, machine learning, signal processing, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Communications, Computational Sensing, Dynamical Systems, Machine Learning, Robotics, Signal Processing
    • Host: Perry Wang
    • Apply Now