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).


  • DA1396: Machine learning for Contact-rich Robotic Manipulation

    • MERL is looking for a highly motivated individual to work on contact-rich robotic manipulation applications. The ideal candidate is expected to have expertise both in machine learning techniques, such as Gaussian Process Regression and Deep Neural Networks, as well as in reinforcement learning algorithms. In addition, having experience with robotic systems would be considered a significant plus. The candidate will be expected to develop novel algorithms and possibly implement them on robotic systems. Proficiency in Python programming is necessary, and experience with ROS would be a plus. The candidate will collaborate closely with MERL researchers. Start date for this internship is flexible, and the duration is expected to be 3-6 months.

    • Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    • Host: Diego Romeres
    • Apply Now
  • DA1367: Safe reinforcement and deep learning algorithms

    • MERL is seeking a motivated and qualified individual to conduct research in safe reinforcement learning (RL) and deep learning algorithms for robotics applications. The ideal candidate should have solid background in RL. Knowledge of deep learning algorithms is a plus. Publication of the results produced during the internship is anticipated. Duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Artificial Intelligence, Control, Robotics
    • Host: Mouhacine Benosman
    • Apply Now
  • CD1401: Formal Synthesis for Planning and Control for Autonomous Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on planning and control by formal methods, in particular temporal logics specifications and their synthesis by mixed-integer inequalities. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) formal methods, particularly temporal logics and signal temporal logics, reachability analysis, abstractions of dynamical systems, hybrid predictive control, and mixed integer programming. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.

    • Research Areas: Control, Optimization, Robotics
    • 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
  • CD1382: Motion Planning in Dynamic Environment

    • MERL is seeking a highly skilled and self-motivated intern to work on motion planning of nonholonomic system in dynamic environments. The ideal candidate should have solid backgrounds in task allocation, scheduling, and motion planning under dynamic and stochastic environment. Excellent coding skill and strong publication records are necessary. 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, Optimization, Robotics
    • Host: Yebin Wang
    • Apply Now
  • CD1400: Autonomous Vehicle Planning and Control

    • The Control and Dynamical Systems (CD) group at MERL is seeking highly motivated interns at different levels of expertise 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 after April 1st, 2020.

    • Research Areas: Artificial Intelligence, Control, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CD1402: Predictive control for Performance and Perception Optimization

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on stochastic planning and control for concurrently achieving control performance while concurrently improving the perception of the environment. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) predictive control or model-based motion planning, stochastic control and estimation, interaction between control and estimation algorithms, control with chance constraints, tube-based control. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.

    • Research Areas: Control, Optimization, Robotics
    • Host: Stefano Di Cairano
    • Apply Now
  • CV1425: Contact implicit manipulation

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

    • Research Areas: Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1375: Computer Vision for Robotic Manipulation

    • MERL is looking for a highly motivated intern to work on computer vision for robotic manipulation. There are several available topics to choose from including active perception, grasp detection, and intent recognition for human-robot interaction. The ideal candidate would be a Ph.D. student with a strong background in computer vision, deep learning, and/or robotics. Proficiency in Python programming is necessary and experience with ROS is a plus. Successful candidate will collaborate with MERL researchers to develop algorithms, conduct experiments, and prepare manuscripts for scientific publications. Start date is flexible and expected duration of the internship is at least 3 months. Interested candidates are encouraged to apply with their recent CV, list of related publications, and/or links to GitHub repositories (if any).

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Siddarth Jain
    • Apply Now