Internship Openings

16 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).


  • 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
    • Position ID: SP1155
    • Contact: Jianlin Guo
    • Email: guo[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • SP1147: Packet separation in IoT random access channel

    • We are looking for a qualified recent PhD graduate or PhD student to conduct research and develop novel algorithms for packet separation in IoT random access channel. The ideal candidate should have solid background in statistical signal processing and sparse recovery methods, as well as familiarity with wireless channel modeling and communications. Strong programming skills in MATLAB are required. Publication of the results produced during the internship is anticipated. The duration of the internship is expected to be 3-6 months, with flexible start date.

    • Research Areas: Communications
    • Position ID: SP1147
    • Contact: Milutin Pajovic
    • Email: pajovic[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • SP1158: Coherent optical transmission systems

    • MERL is seeking an intern to work on systems and subsystems for coherent optical fiber transmission. The ideal candidate would be an experienced PhD student or post-graduate researcher working in optical communications. The candidate should have a detailed knowledge of optical communications systems at the physical layer and digital signal processing for digital coherent communication, with a focus on either optical fiber communication or free space optical communication. Strong programming skills in Matlab are essential. Experience of working in a lab environment would be advantageous. Duration is 3 to 6 months.

    • Research Areas: Communications, Signal Processing
    • Position ID: SP1158
    • Contact: David Millar
    • Email: millar[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • 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
    • Position ID: SP1180
    • Contact: Rui Ma
    • Email: rma[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • SP1240: Cooperative Multi-Robot SLAM

    • We are looking for a qualified individual to assist in the development of multi-robot SLAM algorithms, implement algorithms on multiple robot platforms, and design and conduct experiments. Publication of the internship results at leading venues is expected. A candidate is required to have hands-on experience with implementing algorithms on robot platforms, strong programming skills in ROS/C++/Python, as well as background in SLAM algorithms. The duration of the internship is expected to be 3-6 months, with flexible start date.

    • Research Areas: Communications, Signal Processing
    • Position ID: SP1240
    • Contact: Milutin Pajovic
    • Email: pajovic[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • SA1132: End-to-end acoustic analysis recognition and inference

    • MERL is looking for an intern to work on fundamental research in the area of end-to-end acoustic analysis, recognition, and inference using machine learning techniques such as deep learning. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for high impact publication. The ideal candidate would be a senior Ph.D. student with experience in one or more of source separation, speech recognition, and natural language processing including practical machine learning algorithms with related programming skills. The duration of the internship is expected to be 3-6 months.

    • Research Areas: Speech & Audio
    • Position ID: SA1132
    • Contact: Takaaki Hori
    • Email: thori[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CV1241: Deep Learning for Robotic Vision

    • MERL is seeking a highly skilled and motivated intern to work on deep learning for robotic vision. The ideal candidate should have a solid background in path planning, reinforcement learning, and computer vision as will as experience using a DL framework such as PyTorch, Tensorflow or Caffe. Demonstrated capability in coding algorithms and publishing results in leading conference and journals is a necessity. Senior Ph.D. students in learning, control, computer science, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 6 months.

    • Research Areas: Artificial Intelligence, Computer Vision, Robotics
    • Position ID: CV1241
    • Contact: Alan Sullivan
    • Email: sullivan[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • MP1201: Process Control of Vapor Compression Systems

    • MERL is seeking an intern to develop and experimentally validate control algorithms and optimization strategies for vapor compression systems. The ideal candidate has a solid background in process control, system dynamics and thermodynamics, and experience in implementation, validation and verification of control algorithms. Applicants currently enrolled in graduate programs in chemical, mechanical or electrical engineering (or similar) at leading research universities are encouraged to apply. Proficiency in MATLAB and/or LabVIEW is required. The intern will collaborate with MERL researchers in developing algorithms, conducting experiments, and preparing manuscripts for scientific publications.

    • Research Areas: Multi-Physical Modeling, Control
    • Position ID: MP1201
    • Contact: Dan Burns
    • Email: burns[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • MP1189: nano-particle properties

    • MERL is searching for a graduate student to work on properties of nano-particles. Ideal candidates will have a strong background in physics modeling, particularly for hysteresis phenomena. Experience on Ab Initio computations (including density functional theory for material properties or finite-difference-time-domain for optical property) is a plus but not required. The intern is expected to explain experimental measurements. The expected duration is 3 months. Mitsubishi Electric Research Laboratories, Inc. is an Equal Opportunity Employer. Please see our website http://www.merl.com for information relating to our research, and http://www.merl.com/publications/ to explore our publications.

    • Research Areas: Multi-Physical Modeling, Applied Physics
    • Position ID: MP1189
    • Contact: Chungwei Lin
    • Email: clin[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CD1164: Vehicle control with human factors

    • MERL is seeking a highly motivated individual for collaboration and experimentation on control for steering of automotive vehicles. The successful candidate will have experience in using CarSim or similar software and experience in vehicle dynamics and control and possibly human factors in control.

    • Research Areas: Control
    • Position ID: CD1164
    • Contact: Uros Kalabic
    • Email: kalabic[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CD1139: Control planning and decision making for autonomous vehicles

    • MERL's Mechatronics group is seeking a highly motivated intern for performing research in control, planning and decision making in autonomous vehicles. The ideal candidate is working towards a Ph.D. in mechanical, aerospace, or electrical engineering, or in computer science, and has background in vehicle modeling and control, and decision making by optimization, statistics, or set-based methods. The candidate is expected to possess strong abilities in algorithm development, analysis, and Matlab implementation. The internship start date is flexible and the duration is approximately 3-6 months, with possible extension. Publication of the results produced during the internship is expected.

    • Research Areas: Control
    • Position ID: CD1139
    • Contact: Stefano Di Cairano
    • Email: dicairano[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CD1183: Optimization based Control and Estimation for Autonomous Vehicles

    • MERL is looking for highly motivated individuals to work on the development and implementation of optimization based control and estimation algorithms, including model predictive control (MPC) and/or moving horizon estimation (MHE), for autonomous vehicles. The research will involve some among the following: the study and development of nonlinear optimization techniques for real-time optimal control, the implementation of algorithms for predictive control or state and parameter estimation and the validation of techniques using embedded control hardware and/or experimental data. The ideal candidate should have experience in optimization algorithms, model predictive control and moving horizon estimation, nonlinear vehicle dynamics, ADAS and vehicle control or estimation. PhD students in engineering or mathematics with a focus on optimization algorithms, nonlinear MPC/MHE or vehicle control and estimation are encouraged to apply. Publication of relevant results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab 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 flexible.

    • Research Areas: Control
    • Position ID: CD1183
    • Contact: Rien Quirynen
    • Email: quirynen[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CD1134: Traffic Control

    • MERL is seeking a highly motivated individual for collaboration on control of vehicle traffic. The successful candidate will be an advanced graduate student with extensive knowledge of traffic control, preferably with experience in the following areas: modeling and control of dynamical systems, or autonomous vehicle dynamics and control. The duration of the internship will be at least 3 months.

    • Research Areas: Control, Dynamical Systems
    • Position ID: CD1134
    • Contact: Uros Kalabic
    • Email: kalabic[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • 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
    • Position ID: CD1140
    • Contact: Stefano Di Cairano
    • Email: dicairano[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • CD1119: Provable Estimation for Complex Systems

    • MERL is seeking a motivated and qualified individual to conduct research in estimation theory for complex systems. The ideal candidate should have solid background in estimation theory addressing complexity including partially observable dynamics, hybrid, nonlinearity, and large scale. Senior PhD students in control, mathematics, and related areas are encouraged to apply. Duration is about 3 months.

    • Research Areas: Control
    • Position ID: CD1119
    • Contact: Yebin Wang
    • Email: yebinwang[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.
  • 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
    • Position ID: AL1031
    • Contact: Matt Brand
    • Email: brand[at]merl[dot]com
    • To be considered please send CV and Position ID to the contact email.