Internship Openings

13 / 62 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).


  • 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
  • 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
  • CV1304: Uncertainty Estimation for Deep Network Predictions

    • While deep networks have been highly successful at visual regression problems such as face landmark estimation and skeleton tracking, relatively little work has been done on estimating their prediction error. We are seeking a highly motivated intern to conduct original research in the area of uncertainty estimation for deep network predictions. 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 and machine learning with a strong publication record and experience in deep learning-based facial or body landmark estimation and tracking. Strong programming skills, experience developing and implementing new models in deep learning platforms such as PyTorch and TensorFlow, and broad knowledge of machine learning and deep learning methods are expected.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • 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
  • DA1297: Visuomotor Modelling for Learning Robots

    • The Data Analytics group at MERL is seeking a highly motivated intern to work on the development of dynamical models for robot learning. The target applications will be the model and control of real robotic systems with end-to-end type algorithms. The successful candidate will collaborate with MERL researchers to develop and implement new modelling techniques in high dimensional space (e.g. image space) to be used in a Reinforcement Learning framework, conduct experiments on the robots and achieve scientific contributions for publications and/or patents. Ideal candidate would be senior PhD student with experience in one or more of the following areas: machine learning modelling techniques (such as Gaussian Processes, Deep Learning) and Reinforcement Learning. Strong programming skills in Python and familiarity with ROS are expected. Previous experience in working with robotics platforms and in computer vision projects is a plus.

    • Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    • Host: Diego Romeres
    • Apply Now
  • 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
  • DA1286: Optimization Algorithms

    • The Data Analytics group at MERL is seeking highly motivated intern to work on the development of novel optimization algorithms. The target applications span a broad range of areas including machine learning, scheduling, and transportation. Successful candidate will collaborate with MERL researchers to develop and implement new algorithms, conduct experiments, and prepare results for publication. Ideal candidate would be senior PhD student with experience in one or more of the following areas: machine learning, mathematical optimization. Strong programming skills and fluency in C++/Python are expected. Prior experience with popular optimization packages such as Ipopt, Gurobi, Cplex, PyTorch is a plus. The duration of the internship is expected to be 3 months. Start date is flexible.

    • Research Areas: Artificial Intelligence, Machine Learning, Optimization
    • Host: Arvind Raghunathan
    • Apply Now
  • DA1290: 3D SLAM and Machine Learning for Drones

    • MERL is seeking a motivated and qualified individual to conduct research in 3D SLAM and deep learning for drone applications. The ideal candidate should have solid background in 3D SLAM. Knowledge of deep learning algorithms and experience working with drone testbeds 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, Computer Vision, Robotics
    • Host: Mouhacine Benosman
    • 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
  • CD1295: Modeling and data-assimilation of atmospheric flows

  • CD1298: Theoretical and computational aspects of mean-field control

    • We are looking for a graduate student intern to work on theoretical and computational aspects of mean-field control and mean-field games. An ideal candidate will be a graduate student working on MFC/MFG or Optimal Transport. Expertise in TWO or more of the following areas is required: 1). Optimal control 2). Control of PDEs 3). Geometric methods of dynamical systems theory 4). Statistical Mechanics 5). Stochastic analysis 6). Optimal Transport. Ph.D. students from top programs in engineering, physics, applied math are encouraged to apply. The duration of the internship will be 3-6 months. Publication of results is highly encouraged.

    • Research Areas: Applied Physics, Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
    • Host: Piyush Grover
    • Apply Now
  • CD1296: Optimization and Control of Thermo-fluid Systems

  • CD1259: Cyberphysical Automotive Systems

    • The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on cyber-physical vehicle systems. The research domain includes driving assistance systems, driver-vehicle interaction, connected vehicles, and cyber-security for automotive control systems. Experience with one among particle filtering, model predictive control, constrained control, distributed control is highly desired. Working knowledge of Matlab, Simulink, C/C++, rapid prototyping systems (dSPACE), and vehicle dynamics simulators is required. Experience with CAN bus is a plus. The expected duration of the internship is 3-6 months with flexible start date.

    • Research Areas: Artificial Intelligence, Control, Signal Processing
    • Host: Stefano Di Cairano
    • Apply Now