Internship Openings

10 / 40 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).


  • 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
  • SP1370: Machine Learning based DPD for Power Amplifier

    • 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, Electronic and Photonic Devices, Machine Learning, Signal Processing
    • Host: Rui Ma
    • Apply Now
  • SP1379: Intelligent Brain-Machine Interface

    • The Signal Processing group at MERL is seeking a highly motivated, qualified individual to join our 3-month internship program of research on stressless man-machine interface with multi-modal bio-sensors. The ideal candidate is expected to possess an excellent background in brain-machine interfaces, data analytics, machine learning, sensor design, electro-magnetic analysis, augmented reality, and sensing algorithms. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Signal Processing
    • Host: Toshi Koike-Akino
    • 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
  • SP1368: AI-enhanced security

    • MERL is seeking a highly motivated and qualified intern to work on AI-enhanced security. The candidate is expected to develop innovative AI technologies for cybersecurity applications. Candidates should have strong knowledge and hands on experience in the areas of neural network and learning techniques, such as feature extraction, machine learning, deep learning, shallow learning, and distributed learning. Proficient programming skills with Python, Matlab, and C++, and strong mathematical analysis will be required to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing
    • Host: K.J. Kim
    • 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
  • SP1366: 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
  • CV1364: Graph neural networks for autonomous driving

    • MERL is looking for a self-motivated intern to work on graph neural networks. 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: Computer Vision, Machine Learning, Signal Processing
    • Host: Siheng Chen
    • Apply Now
  • CD1393: Estimation and Learning of Decentralized Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on estimation and learning of decentralized systems. The ideal candidate is a PhD candidate in electrical engineering, statistics, or related fields, and has expertise in some of Kalman filters, particle filters, multiple model filters, Bayesian learning, centralized/decentralized sensor fusion, and optimization-based estimation. Previous experience in any of ground vehicle estimation and satellite navigation systems is a merit. Publication of relevant results in conference proceedings and journals is expected, and so is capability of implementing algorithms in Matlab. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Machine Learning, Signal Processing
    • Host: Karl Berntorp
    • Apply Now
  • CD1391: Algorithms for GNSS localization

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to work on GNSS Positioning and localization. Previous experience with at least some of the GNSSs, particle filtering, interacting multiple model filtering, Kalman-type filtering, and ambiguity resolution is highly desirable. Working knowledge of C/C++ is required, and previous experience with GNSS packages such as RTKLib is highly desired. PhD candidates meeting the above requirements are welcome to apply. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Control, Signal Processing
    • Host: Karl Berntorp
    • Apply Now