Internship Openings

25 Intern positions are currently open.

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 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.


  • 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: Kieran Parsons
    • Apply Now
  • SP1307: Vehicular traffic environment sensing

    • MERL is seeking a highly motivated, qualified intern to join a three month internship program. The ideal candidate will be expected to carry out research on environmental sensing in high frequency bands. The candidate is expected to develop innovative sensing technologies. Candidates should have strong knowledge about neural network and learning techniques, such as machine learning, deep learning, shallow learning, and distributed learning. In addition, understanding of spectrum sensing and wireless communications technologies is necessary. Proficient programming skills with Python, MATLAB, and C++, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1475: Advanced Signal Processing for Metasurface

    • MERL is seeking a highly motivated, qualified intern to join an internship program. The ideal candidate will be expected to carry out research on Advanced Signal Processing for Metasurface. The candidate is expected to develop innovative signal processing for metasurface aided various applications. Candidates should have strong knowledge about electromagnetic field analysis for metasurface, passive beamforming, interference mitigation, and channel estimation. Proficient programming skills with Python, MATLAB, and C++, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. The expected duration of the internship is 3-6 months, with a flexible start date in 2020. 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, Communications, Signal Processing
    • Host: K.J. Kim
    • 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
  • SP1517: AI-based spectrum management for 5G wireless networks and beyond

    • MERL is seeking a highly motivated, qualified intern to join a thirteen weeks internship program. The ideal candidate will be expected to carry out research on emerging 5G wireless networks and beyond for industrial applications. The candidate is expected to develop innovative spectrum-based traffic recognition and optimal scheduling for local spectrum access. Candidates should have strong knowledge about 5G networks, spectrum management, cognitive radio, and neural network. Proficient programming skills with MATLAB, C++, Python (Pytorch), experience with ns-3 simulator, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. 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, Machine Learning, Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1468: Quantum Machine Learning

    • MERL is seeking an intern to work on research for quantum machine learning (QML). The ideal candidate is an experienced PhD student or post-graduate researcher having an excellent background in quantum computing, deep learning, and signal processing. Proficient programming skills with PyTorch, Qiskit, and PennyLane will be additional assets to this position. Also note that we wish to fill this position as soon as possible and expect that the candidate will be available during this fall/winter. 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, Machine Learning, Signal Processing
    • Host: Toshi Koike-Akino
    • Apply Now
  • SP1537: Machine Learning for Wireless Communications

    • MERL is seeking an intern to work on machine learning for wireless communication systems. The ideal candidate would be an experienced PhD student or post-graduate researcher working in wireless communications with a focus on machine learning methods. The candidate should have a detailed knowledge of wireless communications, with some experience in machine learning, MIMO, and/or channel equalization preferred. Strong programming skills in Python and machine learning frameworks are essential. The expected duration of the internship is 3-6 months with flexible start date and length. 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, Machine Learning
    • Host: Ye Wang
    • 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
  • 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
  • SA1686: Multimodal scene understanding

    • We are looking for a graduate student interested in helping advance the field of multi-modal scene understanding, with a focus on detailed captioning of a scene using natural language. 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 deep learning for audio-visual, signal, and natural language processing. The expected duration of the internship is 3-6 months, and 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: Artificial Intelligence, Speech & Audio
    • Host: Chiori Hori
    • Apply Now
  • SA1612: End-to-end speech and audio processing

    • MERL is looking for interns to work on fundamental research in the area of end-to-end speech and audio processing for new and challenging environments using advanced machine learning techniques. The intern will collaborate with MERL researchers to derive and implement new models and learning methods, conduct experiments, and prepare results for high-impact publication. The ideal candidates would be senior Ph.D. students with experience in one or more of automatic speech recognition, speech enhancement, sound event detection, and natural language processing, including good theoretical and practical knowledge of relevant machine learning algorithms with related programming skills. The internship will take place during fall/winter 2021 with an expected duration of 3-6 months and 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: Speech & Audio
    • Host: Takaaki Hori
    • Apply Now
  • SA1689: Audio source separation and sound event detection

    • We are seeking a graduate student interested in helping advance the fields of source separation, speech enhancement, robust ASR, and sound event detection/localization in challenging multi-source and far-field scenarios. 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 some of the following: audio signal processing, microphone array processing, probabilistic modeling, sequence to sequence models, and deep learning techniques, in particular those involving minimal supervision (e.g., unsupervised, weakly-supervised, self-supervised, or few shot learning). The internship will take place during spring/summer 2022 with an expected duration of 3-6 months and 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: Machine Learning, Speech & Audio
    • Host: Gordon Wichern
    • Apply Now
  • MD1693: Aircraft electric propulsion system design

    • MERL is seeking a motivated and qualified individual to conduct research in modeling, simulation and analysis of aircraft electric propulsion system. The ideal candidate should have solid backgrounds in multi-physics modeling and simulation of aircraft electrical propulsion system. Demonstrated experience in modeling and simulation software/language such as Modelica or Simscape is a necessity. Knowledge and experience of NPSS, aircraft dynamics, and aerodynamics is a definite plus. Senior Ph.D. students in aerospace and electrical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3 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: Dynamical Systems, Electric Systems, Multi-Physical Modeling
    • Host: Yebin Wang
    • Apply Now
  • MD1561: Desgn and fabrication of power devices in power electronics or RF

    • MERL is seeking a highly motivated, qualified individual to join our 3-month internship program to carry out research in the area of power electronics and RF semiconductors devices. The ideal candidate should have a significant background in the simulation and design of a 2D and 3D GaN devices using Matlab and TCAD. Proficiency in device semiconductor modeling or hands-on experience in GaN device fabrication processes and a deep knowledge of negative capacitance would be a great asset. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply. 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: Electronic and Photonic Devices
    • Host: Koon Hoo Teo
    • Apply Now
  • MD1300: Compiler Optimizations for Linear Algebra Kernels

    • MERL is looking for a highly motivated individual to work on automatic, compiler based techniques for optimizing linear algebra kernels. The ideal candidate is a Ph.D. student in computer science with extensive experience in compiler design and source code optimization techniques. In particular, the successful candidate will have a strong working knowledge of polyhedral optimization techniques, the LLVM compiler, and Polly. Strong C/C++ skills and knowledge of LLVM at the source level are required. Publication of results in conference proceedings and journals is expected. The expected duration of the internship is 3 months and the start date is flexible.

    • Research Areas: Control, Machine Learning, Optimization
    • Host: Abraham Goldsmith
    • Apply Now
  • MD1679: Machine Learning for Radio Frequency Transmitters

    • MERL is looking for a highly motivated individual to join our internship program for beyond 5G/6G advanced intelligent radio frequency transmitter research. The ideal candidate should be a senior Ph.D. student with rich experience in digital RF technologies with adaptive signal processing and machine learning applications. Knowledge of wireless communication/transceiver architecture, and FPGA/Matlab programming skills are required. Experiences of Digital-pre-distortion algorithms for radio transmitter (PA) linearization are ideal. Good practical laboratory skills are needed. RF semiconductor devices and circuit knowledge is a plus. 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: Electronic and Photonic Devices, Machine Learning, Optimization
    • Host: Rui Ma
    • Apply Now
  • MD1696: Advanced RF Technologies

    • Mitsubishi Electric Research Laboratories (Cambridge, MA) is seeking a highly motivated, qualified individual to join our 3 month internship program of research on advanced RF technologies. The ideal candidate should be a senior Ph.D. student with good experience in microwave power amplifier/RF active circuit design and experiment, RF front end systems. Familiarity with ADS and Matlab is required. Knowledge of radio system architecture and FPGA (signal processing) would be an asset. 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: Communications, Electronic and Photonic Devices, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • MD1694: Path Planning for Articulated Vehicles

    • MERL is seeking a highly skilled and self-motivated intern to work on path/motion planning of articulated vehicles.

      The ideal candidate should have solid backgrounds in path/motion planning, nonlinear geometric control theory, and machine learning. Excellent coding skill and strong publication records are necessary. Senior Ph.D. students in control, electrical engineering, robotics, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 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: Control, Machine Learning, Robotics
    • Host: Yebin Wang
    • Apply Now
  • MD1593: Design Optimization for Electric Machines

    • MERL is seeking a motivated and qualified intern to conduct research on design optimization of electrical machines. The ideal candidate should have solid background and demonstrated research experience in mathematical optimization methods, especially in topology optimization, robust optimization, sensitivity analysis, and machine learning techniques. Hands-on experiences with the implementation of optimization algorithms, machine learning and deep learning methods are highly desirable. Knowledge and experience with electric machine principle, design and finite-element analysis is a strong plus. Senior Ph.D. students in related expertise are encouraged to apply. Start date for this internship is flexible and the duration is about 3-6 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: Artificial Intelligence, Machine Learning, Multi-Physical Modeling, Optimization
    • Host: Bingnan Wang
    • Apply Now
  • MD1697: Integrated design of mechatronic systems

    • MERL is seeking a highly motivated and qualified individual to conduct research in model-based mechatronic system design. The ideal candidate should have solid backgrounds in motor and drives, multi-body dynamics, design optimization, and coding skills. Demonstrated experience on hand-on mechatronic system integration, and simulation/optimization software such as Matlab is a necessity. Ph.D. students in mechanical engineering, robotics, and electrical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3 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: Multi-Physical Modeling, Optimization, Robotics
    • Position ID: MD1697
    • Contact: Yebin Wang
    • Email: yebinwang[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • MD1648: THz Electronic Sensing

    • MERL is looking for a senior Ph.D. student to join our team to conduct application-motivated research and experiments. The candidate must have hands-on practical lab experiment experience on millimeter-wave, sub-THz, or THz for sensing, radar, and other applications. Skills of using RF/Microwave Lab equipment are necessary. Knowledge of solid-state device physics, high frequency, and high speed integrated circuit (IC) chip design, and signal processing is desired. The internship is expected to be 3-6 months, starting date is flexible after September. This internship requires work that can only be done at MERL.

    • Research Areas: Applied Physics, Computational Sensing, Electronic and Photonic Devices
    • Host: Rui Ma
    • Apply Now
  • DA1508: Safe reinforcement learning for real-life applications

    • MERL is seeking a motivated and qualified individual to conduct research in safe reinforcement learning (RL). The ideal candidate should have solid background in RL, e.g. CMDP, and RMDP theories. Knowledge of dynamical system theory and nonlinear control theory is a plus, but not a requirement. Publication of the results produced during the internship is anticipated, e.g., ICML, ICLR, NeurIPS. Duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Artificial Intelligence
    • Host: Mouhacine Benosman
    • Apply Now
  • DA1677: Machine Learning Algorithms for Sequence Prediction

    • MERL is looking for a highly motivated and qualified candidate to work on machine learning algorithms for prediction of spatiotemporal data represented as time series of geospatial locations. The ideal candidate will have solid understanding of sequence prediction algorithms, including transformer neural networks, recurrent neural networks, and other deep neural network models, as well as good foundational knowledge of discrete event systems, including Markov and semi-Markov models. Demonstrated hands-on experience with PyTorch or other Python implementations of such algorithms is required. Additional knowledge of time series analysis and statistical machine learning, as well as experience with tools and methods for geospatial processing would be a plus. PhD students are preferred, but Master's students will be considered, too. The expected duration of the internship is 3-4 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: Data Analytics, Machine Learning
    • Host: Daniel Nikovski
    • Apply Now
  • 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
  • CA1695: Spacecraft Attitude Control

    • MERL is seeking a highly motivated intern for a research position in spacecraft attitude control. The ideal candidate has experience in attitude kinematics and dynamics, computational fluid dynamics (CFD) using OpenFOAM, programming in C++, optimization, and control of rigid bodies and PDEs. Experience in multi-phase flow modeling and volume-of-fluid approach with an emphasis on liquid-gas systems is highly desirable. PhD students in aerospace, mechanical, or electrical engineering are encouraged to apply. Publication of results produced during the internship is expected. The duration of the internship is 3-6 months, and the 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: Control, Dynamical Systems, Multi-Physical Modeling
    • Host: Avishai Weiss
    • Apply Now