Internship Openings

9 / 58 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).


  • SP1430: WiFi Sensing

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in wireless sensing using communication signals such as 5G, WiFi, and Bluetooth. Previous experience on occupancy sensing, people counting, localization, device-free pose/gesture recognition with machine learning approaches is highly preferred. Familiarity with IEEE 802.11 (ac/ad/ay)standards is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, collect real-world channel measurements, 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.

    • Research Areas: Artificial Intelligence, Communications, Computational Sensing, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • SP1414: 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.

    • Research Areas: Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
    • Host: Hassan Mansour
    • Apply Now
  • SP1371: Object Tracking and Perception for Autonomous Driving

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in automotive radar-based object tracking and perception for autonomous driving. Previous experience on multiple (point and extended) object tracking, data association, and data-driven object detection/tracking is highly preferred. Knowledge about automotive radar schemes (MIMO array and waveform modulation (FMCW, PMCW, and OFDM)) and hands-on experience on open automotive datasets are a plus. Knowledge on vehicle dynamics is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, conduct field measurements, data analysis (Python & MATLAB), 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, Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • MP1406: Numerical Analysis of Electric Machines

    • MERL is seeking a motivated and qualified intern to conduct research in the design, modeling and optimization of electrical machines. The ideal candidate should have solid backgrounds in electromagnetic theory, electric machine design, and numerical modeling techniques (including model reduction), research experiences in electric, magnetic, and thermal modeling and analysis of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and optimization techniques is a strong plus. Senior Ph.D. students in electrical or mechanical engineering with related expertise are encouraged to apply. Start date for this internship is flexible and the duration is 3-6 months.

    • Research Areas: Dynamical Systems, Multi-Physical Modeling, Optimization
    • Host: Bingnan Wang
    • Apply Now
  • CD1417: Dynamics and Control of Electric Vehicles

    • MERL is seeking a motivated and qualified individual to conduct research on dynamics and control of electric vehicles. The ideal candidate should have a solid background in vehicle dynamics and control. PhD students in mechanical or electrical engineering with focus on automotive systems are encouraged to apply. The intern will collaborate with MERL researchers in developing nonlinear control algorithms for electric vehicles. Start date for this internship is flexible and the expected duration is approximately 3-6 months.

    • Research Areas: Control, Dynamical Systems
    • Host: Claus Danielson
    • 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
  • CD1383: Collaborative Estimation for Robotic Manipulators

    • MERL is seeking a highly skilled and self-motivated intern to conduct research on condition monitoring for robotic manipulators. The ideal candidate should have solid backgrounds in robotic manipulators, stochastic estimation methods for dynamical systems, and collaborative strategies over multi-agents. Experience of applying machine learning to dynamical systems is a strong plus. Excellent coding skill and strong publication records are necessary. Senior Ph.D. students in control, robotics, or related areas are encouraged to apply. Start date for this internship is flexible, and the expected duration is about 3 months.

    • Research Areas: Dynamical Systems, Machine Learning, Robotics
    • Host: Yebin Wang
    • Apply Now
  • CD1388: Mixed-Integer Optimal Control Algorithms

    • MERL is looking for highly motivated individuals to work on efficient numerical algorithms and applications of mixed-integer optimal control methods. The research will involve some among the following: the study and development of mixed-integer optimization techniques for optimal control, the implementation and validation of algorithms for relevant control applications. The ideal candidate should have experience in branch-and-bound methods and presolve techniques for mixed-integer optimization and/or model predictive control. PhD students in engineering or mathematics with a focus on mixed-integer optimization or numerical optimal control 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 big plus. The expected duration of the internship is 3-6 months and the start date is flexible.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Rien Quirynen
    • Apply Now
  • CD1412: Control of Space Vehicles

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern for a research position in control of space vehicles. The ideal candidate is working towards a Ph.D. in aerospace, mechanical, or electrical engineering, and has background in both optimization-based control and space vehicle dynamics. The candidate is expected to possess strong abilities in algorithm analysis and Matlab implementation. The duration of the internship is approximately 3 months. Publication of results produced during the internship is expected.

    • Research Areas: Control, Dynamical Systems, Optimization
    • Host: Avishai Weiss
    • Apply Now