Internship Openings

22 / 55 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 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

MERL believes that having an internship be located in MERL's office allows for particularly good interaction between you and those that you will be working with at MERL. In addition, some intern projects, e.g., ones that require specialized laboratory equipment, can only be pursued in our office. We expect that all internships during 2022 will be in-person at MERL.

It is of course possible that COVID will take a significant turn for the worse in 2022. If that happens, we will reevaluate our plans and some internships might have to become remote.

It is a requirement at MERL that everyone working in MERL's space must be fully vaccinated. In order for you to have your internship at MERL, you will have to prove that you are fully vaccinated when you arrive at MERL, ie by showing your vaccination card.


  • DA1751: Power Grid Fault Event Detection

    • MERL is seeking a highly motivated and qualified individual to join our summer internship program and conduct research in the area of power grid fault event detection. The ideal candidate should have a solid knowledge of power grid, inverter control and protection, outage analysis, signal processing, and machine learning. Experience with MATLAB or C/C++/Python is required. The duration of the internship is expected to be 3-6 months, and the start date is flexible. Candidates in their senior or junior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Data Analytics, Electric Systems, Machine Learning, Signal Processing
    • Host: Hongbo Sun
    • Apply Now
  • SP1762: Computational Sensing Technologies

    • 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, deep learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/THz imaging, joint communications and sensing, multimodal sensor fusion, object or human tracking, 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.

    • Research Areas: Computational Sensing, Signal Processing
    • Host: Petros Boufounos
    • Apply Now
  • SP1730: Advanced Signal Processing for RF-controlled metasurface

    • MERL is seeking a highly motivated, qualified intern to carry out research on Advanced Signal Processing for RF-controlled meta-surfaces. The candidate is expected to develop innovative signal processing for RF-controlled meta-surfaces aiding various applications. Candidates should have strong knowledge of machine learning, channel estimation, beamforming, interference mitigation, optimization, and electromagnetic field analysis. Proficient programming skills with Python and MATLAB 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.

    • Research Areas: Communications, Machine Learning, Optimization, Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1718: Brain-Machine Interface

  • SP1763: Technologies for 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.

    • Research Areas: Computational Sensing, Signal Processing
    • Host: Petros Boufounos
    • Apply Now
  • SP1752: Machine Learning for Electric Design Automation

    • MERL is seeking a highly motivated and qualified intern to join the Signal Processing group for an internship program. The ideal candidate will be expected to carry out research on machine learning for automated design synthesis to improve hardware efficiency of various digital signal processing algorithms. The candidate is expected to have solid knowledge of deep learning, reinforcement learning, symbolic learning, decision making, and graph neural networks. Hands-on experience of high-level synthesis, FPGA prototyping, verilog, and general digital signal processing is a plus.

    • Research Areas: Artificial Intelligence, Electric Systems, Machine Learning, Signal Processing
    • Host: Toshi Koike-Akino
    • Apply Now
  • SP1734: Robust Machine Learning

    • MERL is seeking a highly motivated and qualified intern to work on robust machine learning techniques. The intern will collaborate with MERL researchers on developing novel approaches to address the problem of adversarial examples. The ideal candidate would have research experience in robust machine learning methods and defenses against adversarial examples. A mature understanding of modern machine learning methods, proficiency with Python, and familiarity with deep learning frameworks are expected. Proficiency with other programming languages and software development experience is a plus. Candidates at or beyond the middle of their Ph.D. program are encouraged to apply.

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing
    • Host: Ye Wang
    • Apply Now
  • SP1747: Learning for Inverse Problems

    • 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. 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.

    • Research Areas: Applied Physics, Computational Sensing, Machine Learning, Optimization, Signal Processing
    • Host: Hassan Mansour
    • Apply Now
  • SP1753: Algorithms for Coherent Imaging Systems

    • MERL is seeking an intern to work on estimation algorithms for coherent optical imaging. The ideal candidate would be a senior PhD student working in coherent imaging. The candidate should have experience in statistical modeling and estimation. A detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR is also preferred. Strong programming skills in MATLAB or Python are essential. Publication of the results produced during our internships is expected. Duration is anticipated to be 3 to 6 months.

    • Research Areas: Computational Sensing, Electronic and Photonic Devices, Signal Processing
    • Host: Joshua Rapp
    • Apply Now
  • SP1748: 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 (e.g., Wi-Fi) and other RF signals (such as millimeter-wave sensing waveforms). Expertise in deep learning in one of the following areas: localization, occupancy sensing, device-free pose/gesture recognition, skeleton tracking, and multi-modal fusion, is highly preferred. Familiarity with IEEE 802.11 (g/n/ac/ad/ay)standards is a plus. Familiarity with python and deep learning libraries is a must. 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. The expected duration of the internship is 3 months with a flexible start date. This internship requires work that can only be done at MERL.

    • Research Areas: Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • SP1733: ML for GNSS-based Applications

    • MERL is seeking a highly motivated, qualified intern to work on machine learning for Global Navigation Satellite System (GNSS) applications. The ideal candidate is working towards a PhD and is expected to develop innovative machine learning technologies to increase accuracy and integrity of GNSS-based positioning systems. Candidates should have strong knowledge about as many as possible of GNSS signal processing for multipath mitigation, handling RINEX data, neural network and learning techniques, such as feature extraction, deep machine learning, reinforcement learning, domain adaptation, and distributed learning. Proficient programming skills with PyTorch, 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: Communications, Dynamical Systems, Machine Learning, Signal Processing
    • Host: K.J. Kim
    • Apply Now
  • SP1750: THz (Terahertz) Sensing

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in THz (Terahertz) sensing. Expertise in statistical inference, unsupervised anomaly detection, and deep learning (spatial-temporal representation learning) is required. Previous hands-on experience in THz data analysis is a plus. Familiarity with python and deep learning libraries is a must. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with collaborators, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date. This internship requires work that can only be done at MERL.

    • Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • 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.

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing
    • Host: Toshi Koike-Akino
    • Apply Now
  • MD1745: Electric machine operation analysis

    • MERL is looking for a self-motivated intern to work on electric machine experiments and signal processing. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in electric machines, power electronics, and signal processing. Experience in dSPACE is required. Proficiency in MATLAB and simulink is necessary. The intern is expected to collaborate with MERL researchers to carry out experiments, analyze experimental data, and prepare manuscripts for scientific publications. The total duration is 3 months. This internship requires work that can only be done at MERL.

    • Research Areas: Data Analytics, Electric Systems, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • MD1746: PWM inverter circuit design

    • MERL is looking for a self-motivated intern to work on PWM inverter drive circuit design and fabrication. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in power electronics. Experience in PWM inverter design, switching loss estimation, and EMI is desired. The intern is expected to collaborate with MERL researchers to design, simulate, and fabricate circuits, carry out experiments, analyze experimental data, and prepare manuscripts for scientific publications. The total duration is 3 months. This internship requires work that can only be done at MERL. This internship requires work that can only be done at MERL.

    • Research Areas: Control, Electric Systems, Signal Processing
    • Host: Dehong Liu
    • 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.

    • Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • MD1761: Blind signal decomposition

    • MERL is seeking a self-motivated intern to work on blind signal decomposition. The ideal candidate would be a senior PhD student with solid background in signal processing, sparse representation, and optimization. Prior experience in array signal processing, compressive sensing, and spectrum analysis is preferred. Skills in Python and/or Matlab are required. The intern is expected to collaborate with MERL researchers to build models, develop algorithms, and prepare manuscripts for scientific publications. The expected duration of the internship is 3 months and the start date is flexible. This internship requires work that can only be done at MERL.

    • Research Areas: Computational Sensing, Optimization, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • MD1757: ML based Digital Pre-distortion (DPD) for PA

    • MERL is looking for a talented intern to work on the next generation Digital-predistortion algorithms for power amplifier linearization such as 5G. The development of a DPD system involves aspects of signal processing and statistical algorithm design, RF components and instrumentation, digital hardware and software. It is therefore both a challenging and intellectually rewarding experience. This will involve MATLAB coding, interfacing to test equipment such as power sources, signal generators and analyzers and construction and calibration of RF component assemblies. The ideal candidate should have knowledge and experience in adaptive signal processing, machine learning, and radio communication. Good practical laboratory skills are needed. RF semiconductor devices and circuit knowledge is a plus. Duration is 3 to 6 months. This internship requires work that can only be done at MERL.

    • Research Areas: Electronic and Photonic Devices, Machine Learning, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • CV1770: Vital signs estimation using computer vision and machine learning

    • MERL is seeking a highly motivated intern to conduct original research in the area of monitoring vital signs such as heart rate, heart rate variability, breathing rate, and blood pressure, from video of a person. the successful candidate will use the latest methods in deep learning, computer vision, and signal processing to derive and implement new models, collect data, conduct experiments, and prepare results for publication, all in collaboration with MERL researchers. The candidate should be a PhD student in computer vision with a strong publication record and experience in computer vision, signal processing, machine learning, and health monitoring. Strong programming skills (Python, Pytorch/Tensorflow, Matlab, C/C++, etc.) are expected.

    • Research Areas: Computer Vision, Machine Learning, Signal Processing
    • Host: Tim Marks
    • Apply Now
  • CA1726: Distributed Estimation for Autonomous Systems

    • MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in developing estimation methods with applications to multi-vehicle positioning. The ideal candidate is a PhD candidate with strong emphasis in estimation and control, and as interest and background in several of: bayesian inference, machine learning, maximum-likelihood estimation, optimization, distributed systems, and vehicle modeling and control. Good programming skills in MATLAB, Python, or C/C++ are required. The expected start of of the internship is in 2022 and flexible for a duration of 3-6 months.

    • Research Areas: Control, Optimization, Signal Processing
    • Host: Karl Berntorp
    • Apply Now
  • CA1727: Learning for Control

    • MERL is looking for highly motivated interns to work with the Control for Autonomy team in the domain of data-based estimation for integration into control, with applications to, e.g., vehicle control. The ideal candidate is working towards a PhD with emphasis on control and has experience in as many as possible of the following topics: statistical signal processing, Bayesian inference, predictive control, stochastic constrained control, statistical learning. Publication of relevant results in conference proceedings or journals is expected. Capability of implementing the designs and algorithms in MATLAB/Python is expected; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is 3-6 months, and the start date is in 2022 but flexible.

    • Research Areas: Control, Machine Learning, Signal Processing
    • Host: Karl Berntorp
    • Apply Now
  • CA1706: Perception-aware vehicle control

    • MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control algorithms accounting for perception of the uncertain surrounding environment. The ideal candidate is expected to be working towards a PhD with strong emphasis in control or planning algorithms, and to have interest and background in as many as possible of: predictive control algorithms for linear and nonlinear systems, stochastic constrained control, e.g., chance constraints, stochastic optimization, statistical estimation, perception system modeling, and vehicle modeling and control. Good programming skills in MATLAB, Python or C/C++ are required. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.

    • Research Areas: Control, Optimization, Signal Processing
    • Host: Stefano Di Cairano
    • Apply Now