Internship Openings

17 / 67 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).

Rising to the challenges of COVID-19

The COVID pandemic has impacted every aspect of life-how we live, work, and interact. At MERL, we are committed to maintaining our internship program through these challenging times.

MERL continues to actively seek candidates for research internships -- some of the posted positions are immediately available, while others target the summer of 2021. Please consider applying for positions of interest. Our researchers will follow up to schedule an interview by phone or video conference for qualified candidates.

Due to the situation with the COVID-19 pandemic, our current internships are mostly remote. Next summer we hope the situation will be better and our internships will be at MERL, but if it is not, most internships will continue to be remote. However, some of the internships require onsite work. Please check for any specific requirements for onsite work in the job description.


  • CV1579: Pose Estimation for Robotic Manipulation

    • MERL is looking for a highly motivated and qualified intern to work on developing algorithms for estimating pose for robotic manipulation. The ideal candidate would be a current Ph.D. student with a strong background in computer vision, deep learning, and robotics. Familiarity with machine learning/AI is required, and familiarity with reinforcement learning will be valued. Proficiency in Python programming is necessary and experience in working with a physics engine simulator like Mujoco or pyBullet is a plus. A successful candidate will collaborate with MERL researchers and publication of the relevant results is expected. Start date is flexible and the expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    • Host: Jeroen van Baar
    • Apply Now
  • CV1569: Robot learning from videos of human demonstrations

    • MERL is looking for a highly motivated and qualified intern to work on developing algorithms for robot learning from videos of human demonstrations. The ideal candidate would be a current Ph.D. student with a strong background in computer vision, deep learning, and robotics. Familiarity with imitation learning, learning from demonstrations (LfD), reinforcement learning, and machine learning for robotics will be valued. Proficiency in Python programming is necessary and experience in working with a physics engine simulator like Mujoco or pyBullet is a plus. A successful candidate will collaborate with MERL researchers and publication of the relevant results is expected. Start date is flexible and the expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    • Host: Jeroen van Baar
    • Apply Now
  • CV1534: Video Anomaly Detection

    • MERL is looking for a self-motivated intern to work on the problem of video anomaly detection. The intern will help to develop new ideas for improving the state of the art in detecting anomalous activity in videos. The ideal candidate would be a Ph.D. student with a strong background in machine learning and computer vision and some experience with video anomaly detection in particular. Proficiency in Python programming and Pytorch/Tensorflow is necessary. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The internship is for 3 months and the start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Machine Learning
    • Host: Mike Jones
    • Apply Now
  • CV1546: Vibration analysis in video sequences

    • MERL is looking for a self-motivated intern to work on vibration analysis in video sequences. The ideal candidate would be a Ph.D. student with a strong background in machine learning, optimization and computer vision. Experience in computational photography and MATLAB/Python is a plus. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The internship is for a minimum of 3 months and the start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Machine Learning, Optimization
    • Host: Jeroen van Baar
    • Apply Now
  • CV1548: Robotic manipulation using tactile perception

    • The Computer Vision group at MERL is offering an internship opportunity to a highly skilled PhD student to work on robotic manipulation using multimodal perception. Candidates should have a solid understanding of contact mechanics, path planning and dexterous manipulation. The intern will deploy the algorithms on physical robots. Strong programming skills are required, including MuJoCo, ROS, C++, Python. Duration and start dates are flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1568: Uncertainty Estimation in 3D Face Landmark Tracking

    • We are seeking a highly motivated intern to conduct original research extending MERL's work on uncertainty estimation in face landmark localization (the LUVLi model) to the domains of 3D faces and video sequences. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The candidate should be a PhD student in computer vision and machine learning with a strong publication record. Experience in deep learning-based face landmark estimation, video tracking, and 3D face modeling is preferred. Strong programming skills, experience developing and implementing new models in deep learning platforms such as PyTorch, 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
  • CV1552: Multimodal Reasoning

    • MERL is looking for a self-motivated intern to work on problems at the intersection of video understanding, audio processing, and language models. The ideal candidate would be a PhD student with a strong mathematical background in machine learning and computer vision. The candidate must have prior experience in using deep learning methods for image and video representations (such as using scene graphs) and deep audio analysis (such as source separation, localization, etc.). Proficiency in Python and flexibility in using different deep learning software (especially Pytorch) is expected. The intern is expected to collaborate with computer vision and speech teams at MERL to develop algorithms and prepare manuscripts for scientific publications. The internship is for 3 months with flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
    • Host: Anoop Cherian
    • Apply Now
  • CV1567: Generative Adversarial Networks (GANs) for 3D face generation

    • MERL is seeking a highly motivated intern to conduct original research in the area of generative adversarial networks for realistic 3D face generation. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The candidate should be a PhD student in computer vision with experience in GANs and related deep learning methods, as well as good general knowledge in machine learning and a strong publication record. Previous experience with 3D face models and video generation is preferred. Strong programming skills in Python and flexibility working across various deep learning platforms (e.g., PyTorch and TensorFlow) are expected.

    • Research Areas: Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now
  • CV1540: Computer Vision for Biased or Scarce Data

    • MERL is looking for a self-motivated intern to work on data scarcity and bias issues for computer vision. The topics in the scope include (but not limited to): domain adaptation, generative modeling, transfer/low-shot/unsupervised learning, multi-model or multi-modal fusion or distillation under limited data, etc. The ideal candidate would be a PhD student with a strong background in computer vision and machine learning. Proficiency in Python programming and familiarity in at least one deep learning framework are necessary. The ideal candidate is expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The duration of the internship is ideally to be at least 3 months with a flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Kuan-Chuan Peng
    • Apply Now
  • CV1570: Health monitoring from video

    • MERL is seeking a highly motivated intern to conduct original research in the area of monitoring vital signs, such as heart rate and heart rate variability, from video of a person. The successful candidate will collaborate with MERL researchers to derive and implement new models, collect data, conduct experiments, and prepare results for publication. The candidate should be a PhD student in computer vision with a strong publication record and experience in computer vision, signal processing, machine learning, and health monitoring. Strong programming skills (Python, Matlab, C/C++, etc.) are expected.

    • Research Areas: Computer Vision, Machine Learning, Signal Processing
    • Host: Tim Marks
    • Apply Now
  • CV1541: Computer Vision for Robotic Manipulation

    • MERL is looking for a highly motivated and qualified intern to work on computer vision for robotic manipulation. The ideal candidate would be a current Ph.D. student with a strong background in computer vision, deep learning, and/or robotics. There are several available topics for consideration including learning for object manipulation, grasp detection and regrasping, pose estimation, and intent recognition for human-robot interaction. The internship requires development of novel algorithms which can be implemented and evaluated on a robotic test-bed. Experience in working with a physics engine simulator like Mujoco, pyBullet, or Gazebo is required. Proficiency in Python programming is necessary and experience with ROS is a plus. Successful candidate will collaborate with MERL researchers and publication of the relevant results is expected. Start date is flexible and expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and list of publications in related topics. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Siddarth Jain
    • Apply Now
  • CV1535: Exploring Kervolutional Neural Networks

    • MERL is seeking an intern to conduct research in the area of neural networks with nonlinear kernel activation functions (kervolutional networks) for applications in computer vision. The ideal candidate is a PhD student with experience in deep learning and computer vision and a strong publication record at top-tier venues. Prior experience in the design of novel network architectures and knowledge of kervolutional networks is strongly preferred. Very good Python and Pytorch/Tensorflow skills are required. Publication of results in conference proceedings and journals is expected. The expected duration of the internship is 3 months and the start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Machine Learning
    • Host: Mike Jones
    • Apply Now
  • CV1553: Graph Representations for Action Recognition

    • MERL is looking for a self-motivated intern to work on problems at the intersection of video understanding and graph representation learning for solving action recognition problems. The ideal candidate would be a senior year (>=3) PhD student with a strong mathematical background in machine learning and computer vision and who has published at least one paper in a top-tier machine learning or computer vision venue (NIPS/CVPR/ECCV/ICCV/ICML/PAMI etc.). The candidate must have prior experience in using deep learning methods for video understanding (such as action recognition, scene graph representations, etc.) and language models (such as in visual question answering or captioning). Proficiency in Python and flexibility in using different deep learning software (such as Pytorch) is expected. The internship is for 3 months with flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Anoop Cherian
    • Apply Now
  • CV1586: Cross-modal knowledge distillation

    • MERL is seeking an intern to conduct research in the area of cross-modal knowledge distillation (RGB to IR, RGB to Lidar etc.) for applications in computer vision. The ideal candidate is a senior PhD student with experience in deep learning and computer vision and a good publication record at top-tier venues. Prior knowledge and experience with knowledge distillation and multiple modalities strongly preferred. Very good Python and Pytorch/Tensorflow skills are required. Publication of results in conference proceedings and journals is expected. The expected duration of the internship is 3 months and the start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Suhas Lohit
    • Apply Now
  • CV1545: Multi-modal Perception for Robotic Tool Manipulation

    • MERL is looking for a self-motivated intern to work on multi-modal perception for robotic tool manipulation. The intern will help to develop new ideas for improving the state of the art. The ideal candidate would be a Ph.D. student with a strong background in machine learning and computer vision. Experience in robotics, reinforcement learning and physics engines (MuJoCo) is desired. Proficiency in Python programming and Pytorch/Tensorflow is required. You are expected to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The internship is for a minimum of 3 months and the start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computer Vision, Machine Learning, Robotics
    • Host: Jeroen van Baar
    • Apply Now
  • SP1551: Algorithms for Large-Scale Optimal Transport

    • The Computational Sensing team at MERL is seeking motivated individuals to develop scalable optimal transport algorithms. Ideal candidates should be Ph.D. students with research experience in optimal transport and scalable optimal transport algorithms. Experience with GPU implementations is a plus. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Computational Sensing, Computer Vision, Machine Learning, Optimization, Signal Processing
    • Host: Yanting Ma
    • Apply Now
  • SP1585: Three dimensional Imaging from Compton Camera

    • The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that reconstruct a three dimensional distribution of a radioactive source when observed using a Compton camera. The project goal is to improve the performance and develop an uncertainty analysis of these algorithms. Ideal candidates should be Ph.D. students and have solid background and publication record in 3D Compton imaging. Experience in computational tomography, imaging inverse problems, and large-scale optimization is also preferred. 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. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • Research Areas: Applied Physics, Computational Sensing, Computer Vision, Machine Learning, Optimization, Signal Processing
    • Host: Hassan Mansour
    • Apply Now