Internship Openings

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


  • DA1289: Robot Learning

    • MERL is looking for a highly motivated intern to work on developing algorithms for robot learning. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The candidate should have a strong background in reinforcement learning, Imitation Learning (or Learning from Demonstrations, LfD), machine learning and robotics. Prior experience of working with robotic systems is required. The candidate should be comfortable implementing the developed algorithms in Python and should have prior experience working with ROS. Prior exposure to deep learning and hands-on experience with packages such as Keras, TensorFlow, or Theano is a plus. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, Operations Research, Statistics, Applied Mathematics, or a related field, with relevant publication record. Expected duration of the internship is at least 3 months. Interested candidates are encouraged to apply with their recent CV with list of related publications and links to GitHub repositories (if any).

    • Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    • Host: Devesh Jha
    • Apply Now
  • CD1324: Extended Object Tracking

    • The Control and Dynamical Systems group at MERL is seeking a highly motivated intern to conduct fundamental research in extended object tracking with possible applications to autonomous driving. Previous experience on extended object tracking algorithms based on any of extended/unscented Kalman Filtering, particle filtering, interacting multiple model (IMM) tracking, probability hypothesis density (PHD) filtering, Random Finite Sets, data association, and jointly data association and prediction/filtering (joint probability data association (JPDA), multi-hypothesis tracking (MHT) is highly preferred. Ph.D. students with research focuses on statistical signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with flexible start date, with possible extension.

    • Research Areas: Control, Dynamical Systems, Signal Processing
    • Host: Jay Thornton
    • Apply Now
  • CD1255: Speed-sensorless motor control

    • MERL is seeking a motivated and qualified individual to conduct research in control of electromechanical systems. The ideal candidate should have solid backgrounds in control and estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is around May 2019 and the duration is 3 months.

    • Research Areas: Control, Dynamical Systems, Electric Systems
    • Host: Yebin Wang
    • Apply Now
  • CD1323: Bayesian Inference and Learning

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to advance the frontiers in the intersection of bayesian inference and learning. The ideal candidate has previous experience with at least some of sequential Monte Carlo methods, Gaussian processes, Kalman filtering, and target tracking. The candidate is expected to possess strong abilities in algorithm development and analysis. The internship start date is flexible. The duration is approximately 3 months, with possible extension. Publication of the results produced during the internship is expected.

    • Research Areas: Dynamical Systems, Machine Learning, Signal Processing
    • Host: Jay Thornton
    • Apply Now
  • CD1260: Model Predictive Control of Hybrid Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on hybrid model predictive control. The scope of work includes the development of model predictive control algorithms for hybrid dynamical systems, switched systems, and quantized systems, analysis and property proving, and applications in automotive, space systems, and energy systems. PhD students with expertise in some among control, optimization, model predictive control and hybrid systems, and with working knowledge of Matlab implementation are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1300: 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: Bram Goldsmith
    • Apply Now
  • CD1257: Autonomous vehicles Planning and Control

    • The Control and Dynamical Systems (CD) group at MERL is seeking highly motivated interns at varying expertise levels to conduct research on planning and control for autonomous vehicles. The research domain includes algorithms for path planning, vehicle control, high level decision making, sensor-based navigation, driver-vehicle interaction. PhD students will be considered for algorithm development and analysis, and property proving. Master students will be considered for development and implementation in a scaled robotic test bench for autonomous vehicles. For algorithm development and analysis it is highly desirable to have deep background in one or more among: sampling-based planning methods, particle filtering, model predictive control, reachability methods, formal methods and abstractions of dynamical systems, and experience with their implementation in Matlab/Python/C++. For algorithm implementation, it is required to have working knowledge of Matlab, C++, and ROS, and it is a plus to have background in some of the above mentioned methods. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Artificial Intelligence, Control, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1274: Motion Planning and Experiment

    • MERL is seeking a highly skilled and motivated intern to work on motion planning and tracking control of nonholonomic systems in dynamic environments. The ideal candidate should have solid backgrounds in motion planning algorithms, their implementation, and experiment validation. Demonstrated capability in strong coding and publishing results in leading conference and journals is a necessity. Senior Ph.D. students in control, computer science, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 months.

    • Research Areas: Control, Robotics
    • Host: Yebin Wang
    • Apply Now
  • CD1140: MPC-based modular control architectures

    • MERL's Mechatronics group is seeking a highly motivated intern for performing research in Optimization based modular control architectures. The ideal candidate is working towards a Ph.D. in electrical, mechanical, or aerospace engineering, or in computer science, and has background in model predictive control, optimization, set-based methods, and modular control architectures. The candidate is expected to possess strong abilities in theorem proving, and algorithm development, analysis, and Matlab implementation. The internship start date is flexible and the duration is approximately 3 months, with possible extension. Publication of the results produced during the internship is expected.

    • Research Areas: Control
    • Host: Stefano Di Cairano
    • Apply Now
  • MP1262: Thermal modeling for electric motors

    • MERL is looking for a qualified intern to conduct research on thermal modeling and temperature estimation for electric motors. The ideal candidate should have solid background in the physics and engineering of electric machines, in particular the magnetic field calculations, and loss modeling. Related experience on control and estimation theory is a plus. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. Senior PhD students in electrical engineering, mechanical engineering, and other related areas are encouraged to apply. The duration of the internship is about 3 months.

    • Research Areas: Applied Physics, Dynamical Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • MP1263: Fault analysis for electric motors

    • MERL is seeking a highly motivated intern to conduct research in electric machine fault analysis. The ideal candidate should be a senior Ph. D student in Electrical Engineering or related discipline with a solid background in the physics and engineering of electric motors, and early fault detection. Knowledge and experience in electric motor modeling and machine learning are desired. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. The duration of internship is expected to be 3 months and start date is flexible.

    • Research Areas: Applied Physics, Electric Systems, Multi-Physical Modeling
    • Host: Bingnan Wang
    • Apply Now
  • MP1248: Realtime Optimization and Control

    • MERL is seeking an intern to develop realtime optimization strategies to maximize the performance of vapor compression systems. The ideal candidate has a strong theoretical background in extremum seeking, nonlinear and adaptive control, and optimization. Proficiency in MATLAB, Python or Julia is required. Senior graduate students in engineering or mathematics programs at leading research universities are sought. The intern will collaborate with MERL researchers in developing new algorithms, conducting experiments, and preparing manuscripts for scientific publications. The expected duration is roughly three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • MP1337: control of quantum system

    • Quantum control steers the wave function to the target one by properly choosing the control Hamiltonian. MERL is seeking a highly motivated intern to conduct research in the area of quantum control. The ideal candidate would be a PhD student who is familiar with geometric control (math or control background) and/or qubits interacting with environments (physics background). Strong programming skills in coding (Python, C.. etc) are expected.

    • Research Areas: Applied Physics, Control
    • Host: Chungwei Lin
    • Apply Now
  • MP1249: Control of Systems with Hybrid Dynamics

    • MERL is seeking an intern to develop optimal control strategies for mode-switching vapor compression systems characterized by discrete changes in dynamics. The ideal candidate has a strong background in hybrid systems, optimization, and event-based control. Proficiency in MATLAB, Python or Julia is required. Senior students enrolled in doctoral programs in engineering, applied mathematics or related fields are encouraged to apply. It is expected that the intern will assist in preparation of results for publication in scientific venues. The duration of the internship is approximately three months.

    • Research Areas: Control, Multi-Physical Modeling, Optimization
    • Host: Dan Burns
    • Apply Now
  • AL1031: Distributed auctions for network welfare maximization

    • We are looking for a talented individual to collaborate and facilitate research on new algorithms in mechanism design and distributed auctions. Responsibilities will include mathematical modeling, algorithm design, software prototyping, and running Monte Carlo simulations in a network traffic domain. Candidates should be strong scientific programmers and have some background in numerical optimization, simulation design, and auction theory.

    • Research Areas: Optimization
    • Host: Matt Brand
    • Apply Now
  • SP1305: Intelligent error correction coding

    • The Signal Processing group at MERL is seeking a highly motivated, qualified individual to join our 3-month internship program of research on error correction coding for digital communications. The ideal candidate is expected to possess an excellent background in channel coding theory, source coding, information theory, coded modulation design, signal processing, and machine learning. Strong C/C++ skill and GPU/FPGA acceleration are plus. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications
    • Host: Toshi Koike-Akino
    • Apply Now
  • SP1330: Wave-based Inverse Scattering

    • The Computational Sensing team at MERL is seeking a motivated and qualified individual to conduct research on computational imaging through scattering media under wave-based forward models. The ideal candidate should be a Ph.D. student and have a solid background and publication record in imaging inverse problems, large-scale optimization, blind inverse scattering, and/or radar imaging. Experience with experimentally measured data is desirable. Publication of the results produced during the internship is expected. The duration of the internship is anticipated to be 3-6 months. Start date is flexible.

    • Research Areas: Computational Sensing
    • Host: Hassan Mansour
    • Apply Now
  • SP1329: Tomographic Ionosphere Imaging

    • MERL is seeking a highly motivated intern to conduct research on ionospheric monitoring and forecasting. The ideal candidate should be a Ph.D. student and have a solid background and publication record in tomographic imaging, imaging inverse problems, analysis of inversion algorithms, and/or convex optimization. Experience with deriving recovery guarantees for real tomographic imaging systems is highly desirable. Familiarity with GNSS-based ionospheric density measurement methodologies is desirable. Publications of the results produced during the internship is expected. The duration of the internship is expected to be three months.

    • Research Areas: Computational Sensing
    • Host: Hassan Mansour
    • Apply Now
  • SP1301: Photonic Integrated Circuits Design and Evaluation

    • MERL is seeking a highly motivated, qualified individual to join our internship program and conduct research in the area of photonic integrated circuits and Nanophotonics. The ideal candidate should have a strong background in the simulation, design, and testing of active and passive devices for optical communication, as well as deep neural network. Experience in FDTD, Matlab, Lumerical, silicon photonics, photonic, crystal, optimization algorithms, deep learning, machine learning, photonic device fabrication/measurements, and InP and silicon photonic MPW would be considered an asset. Candidates who hold a Ph.D. or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Artificial Intelligence, Electronic and Photonic Devices
    • Host: Keisuke Kojima
    • 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
  • SP1180: Advanced Phased Array Antenna

    • MERL is looking for a highly motivated, and qualified individual to join our internship program of advanced phased array research. The ideal candidate should be a senior Ph.D. student with rich experience in beam forming technologies. Knowledge of wireless communication, transceiver architecture, and digital signal processing, FPGA and/or Matlab programming skills are required. RF circuits knowledge will be a plus. Duration is 3-6 months.

    • Research Areas: Communications, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • SP1155: Coexistence of the Heterogeneous Wireless Technologies

    • MERL is seeking a highly motivated, qualified intern to join the Electronics and Communications group for a three month internship program. The ideal candidate will be expected to carry out research on coexistence of the heterogeneous wireless technologies in the Sub-1 GHz (S1G) band. The candidate is expected to develop innovative coexistence technology for IEEE 802.15.4g to mitigate interference caused by other S1G technologies such as IEEE 802.11ah, LoRa and SigFox. The candidates should have knowledge of 802.15.4g and 802.11ah protocols. Additionally, the candidate should also be familiar with NS3 simulators. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Signal Processing
    • Host: Jianlin Guo
    • Apply Now
  • SP1251: Digital Predistortion (DPD) of power amplifiers

    • 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.

    • Research Areas: Communications
    • Host: Rui Ma
    • Apply Now
  • SP1267: Signal spectrum analysis

    • MERL is looking for a self-motivated intern to work on signal spectrum analysis. The ideal candidate would be a senior Ph.D. student with strong background in signal processing, compressive sensing, and mathematics. Proficiency in MATLAB and Python programming is necessary. Experience in analyzing real experimental data or detecting weak signal in noisy environment is a great asset. The intern is expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computational Sensing, Optimization, Signal Processing
    • Host: Dehong Liu
    • Apply Now
  • SP1278: Low Latency Wireless Networking

    • MERL is seeking a highly motivated, qualified intern to join the Signal Processing group for a three month internship program. The ideal candidate will be expected to carry out research on low latency networking. The candidate is expected to develop innovative low latency technology in wireless networks. The candidates should have knowledge of low latency networking such as time sensitive networking. Knowledge of wireless network standards such as IEEE 802.11 and simulation tools such as OMNeT++ is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Communications, Machine Learning, Multi-Physical Modeling
    • Host: Jianlin Guo
    • Apply Now
  • CV1283: Understanding of Deep Learning

    • MERL is looking for a self-motivated intern to work on understanding of deep learning. The ideal candidate would be a Ph.D. student with a strong background in machine learning, optimization and computer vision. Proficiency in deep learning toolbox such as PyTorch and Tensorflow is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Computer Vision, Machine Learning, Optimization
    • Host: Ziming Zhang
    • Apply Now
  • CV1269: Machine Learning for Computer Vision

    • MERL is looking for a self-motivated intern to work on machine learning for computer vision. There are several available topics to choose from. The ideal candidate would be a Ph.D. student with a strong background in machine learning and computer vision. Proficiency in Python programming is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. Start date is flexible.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Jeroen van Baar
    • Apply Now
  • CV1338: Robot control algorithms

    • The Computer Vision group at MERL is offering and internship opportunity to a highly skilled graduate student to work on robotic control. Candidates should have a solid understanding of kinematics, path planning with collision avoidance and control theory. The intern will deploy control software on physical robots. Strong programming skills are required, including ROS, Python and C++. Duration and start dates are flexible.

    • Research Areas: Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1303: Generative Adversarial Networks (GANs)

    • Generative adversarial networks (GANs) and related methods have generated much excitement for their ability to synthesize images and data that appear remarkably realistic. MERL is seeking a highly motivated intern to conduct original research in the area of generative adversarial networks. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The ideal candidate would be a senior PhD student in computer vision with experience in GANs and related deep learning methods, as well as strong general knowledge in machine learning. Strong programming skills in Python, flexibility working across various deep learning platforms (e.g., TensorFlow and PyTorch), and previous experience coding GANs are expected.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now
  • SA1320: Deep Network Information Security

    • We are seeking graduate students interested in helping advance the field of network and information security 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 deep networks, natural language processing, and network security. The duration of the internship is expected to be 3-6 months. The internship can be scheduled either during the summer or at another time of year.

    • Research Areas: Machine Learning, Speech & Audio
    • Host: Bret Harsham
    • Apply Now