Internship Openings

13 / 47 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 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

MERL believes that having an internship be located in MERL's office allows for particularly good interaction between you and those that you will be working with at MERL. In addition, some intern projects, e.g., ones that require specialized laboratory equipment, can only be pursued in our office. Going forward, we expect that all internships will be in-person at MERL. If health and safety concerns do not permit this, we will reevaluate our plans and some internships might have to become remote.

It is a requirement at MERL that everyone working in MERL's space must be fully vaccinated. In order for you to have your internship at MERL, you will have to prove that you are fully vaccinated when you arrive at MERL, i.e., by showing your vaccination card.


  • ST1968: Integrated Sensing and Communication (ISAC - WLAN Sensing)

    • The Computational Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research in integrated sensing and communication (ISAC) with a focus on signal processing for WLAN sensing. Expertise in waveform/sequence optimization, integrated precoding for ISAC, and ToF-Doppler-Angle spectrum estimation using Wi-Fi packets is highly desired. Familiarity with IEEE 802.11 (ac/ax/ad/ay) standards is a plus. Knowledge of Wi-Fi-based localization, occupancy sensing, device-free pose/gesture recognition, skeleton tracking, and multi-modal fusion is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, and prepare results for publication. 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, Robotics, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • ST1967: Deep Learning for Radar Perception

    • The Computation Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research in automotive radar perception. Expertise in deep learning-based object detection, multiple object tracking, data association, and representation learning (detection points, heatmaps, and raw radar waveforms) is required. Previous hands-on experience on open automotive datasets is a plus. Familiarity with the concept of FMCW, MIMO, and range-Doppler-angle spectrum is an asset. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with MERL in-house testbed, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.

    • Research Areas: Artificial Intelligence, Computational Sensing, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • ST1750: THz (Terahertz) Sensing

    • The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in THz (Terahertz) sensing. Expertise in statistical inference, unsupervised anomaly detection, and deep learning (spatial-temporal representation learning) is required. Previous hands-on experience in THz data analysis is a plus. Familiarity with python and deep learning libraries is a must. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with collaborators, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.

    • Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Optimization, Signal Processing
    • Host: Perry Wang
    • Apply Now
  • CI1946: Robust, Private, and Efficient Machine Learning

    • MERL is seeking highly motivated and qualified interns to work on fundamental machine learning techniques for robustness, privacy, and efficiency. The ideal candidates would have significant research experience in one or more of the following topics: robust machine learning methods, defenses against adversarial examples, privacy issues in machine learning, membership inference attacks, federated/distributed learning, and/or efficient/Green AI. 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. Multiple positions are available throughout 2023 (Spring/Summer of course, but also as early as January), with expected durations of 3-6 months and flexible start dates.

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing
    • Host: Ye Wang
    • Apply Now
  • CI1950: Quantum Machine Learning

    • MERL is seeking an intern to work on research for quantum machine learning (QML). The ideal candidate is an experienced PhD student or post-graduate researcher having an excellent background in quantum computing, deep learning, and signal processing. Proficient programming skills with PyTorch and PennyLane will be additional assets to this position.

    • Research Areas: Artificial Intelligence, Machine Learning, Signal Processing
    • Host: Toshi Koike-Akino
    • Apply Now
  • DA1976: Hierarchical Reinforcement Learning

    • MERL is looking for a highly motivated individual to work on hierarchical reinforcement learning for robotic applications. The research will develop novel algorithms for hierarchical reinforcement learning and evaluate them on challenging long horizon robotic problems. The ideal candidate must have experience in either one or multiple of the following topics: (Deep) Reinforcement learning, Hierarchical RL, policy optimization and Markov Decision Processes (MDPs). Senior PhD students in machine learning and engineering with a focus on Reinforcement Learning are encouraged to apply. Prior experience working with physics engines like Mujoco, Bullet, etc. is required. A successful internship will result in submission of results to peer-reviewed conference and journals. Good coding skills in Python and state-of-the-art RL environments (e.g., RL Bench) is required. The expected duration of internship is 3-4 months and the start date is flexible. This internship is preferred to be onsite at MERL.

    • Research Areas: Artificial Intelligence, Machine Learning, Optimization, Robotics
    • Host: Devesh Jha
    • Apply Now
  • DA1935: Robot Learning Algorithms

    • MERL is looking for a highly motivated and qualified PhD student in the areas of machine learning and robotics, to participate in research on advanced algorithms for learning control of robots and other mechanisms. Solid background and hands-on experience with various machine learning algorithms is expected, and in particular with deep learning algorithms for image processing and object detection. Exposure to deep reinforcement learning and/or learning from demonstration is highly desirable. Familiarity with the use of machine learning algorithms for system identification of mechanical systems would be a plus, along with background in other areas of automatic control. Solid experimental skills and hands-on experience in coding in Python and PyTorch are required for the position. Some familiarity with classical mechanics and computational physics engines would be helpful, but is not required. The position will provide opportunities for exploring fundamental problems in incremental learning in humans and machines, leading to publishable results. The starting date of the internship is flexible, and applications outside of the peak summer season are encouraged, too.

    • Research Areas: Artificial Intelligence, Computer Vision, Control, Machine Learning, Robotics
    • Host: Daniel Nikovski
    • Apply Now
  • DA1963: Multimodal understanding for robotic manipulation tasks

    • MERL is looking for a self-motivated intern to work on multimodal reasoning problems for robotic manipulation using vision and large-language models. The ideal candidate would be a PhD student with strong mathematical background and peer-reviewed publications in machine learning/reinforcement learning/imitation learning, robotic manipulation, and experience in working with training deep models on large scale computer vision and language models.
      Proficiency in PyTorch, robotic simulators and working with physical robots is expected. The intern will conduct original research with MERL researchers towards scientific publications. The expected duration of internship is 3-4 months with start date in May/June 2023. This internship is preferred to be onsite at MERL.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics, Speech & Audio
    • Host: Devesh Jha
    • Apply Now
  • CV1912: Multimodal Embodied AI

    • MERL is looking for a self-motivated intern to work on problems at the intersection of visual understanding, audio processing, language models, and embodied navigation AI (see our recent NeurIPS 2022 paper for the context). The ideal candidate would be a senior PhD student with a strong background in machine learning and computer vision, as demonstrated by top-tier publications. The candidate must have prior experience in developing deep learning methods for audio-visual-language data. Expertise in popular embodied AI simulation environments as well as a strong background in reinforcement learning will be beneficial. The intern is expected to collaborate with researchers in computer vision and speech teams at MERL to develop algorithms and prepare manuscripts for scientific publications.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics, Signal Processing
    • Host: Anoop Cherian
    • Apply Now
  • CV1913: Roadway Maintenance Using Computer Vision

    • MERL is looking for a self-motivated intern to work on roadway maintenance using computer vision. The relevant topics include (but not limited to): road defect localization and classification, detection of key objects in road scenes, and pavement surface evaluation. Candidates with experience in road defect detection and object detection in road scenes are strongly preferred. The ideal candidate would be a PhD student with a strong background in computer vision and machine learning, and the candidate is expected to have published at least one paper in a top-tier computer vision, machine learning, or artificial intelligence venues, such as CVPR, ECCV, ICCV, ICML, ICLR, NeurIPS, or AAAI. Proficiency in Python programming and familiarity in at least one deep learning framework are necessary. The ideal candidate is required 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.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Kuan-Chuan Peng
    • Apply Now
  • CV1938: Component transfer learning for RL and robotic applications

    • MERL is offering a new research internship opportunity in the field of Transfer Learning for Deep RL. The position requires a strong background in Deep RL, excellent programming skills and experience with robotics is preferred. The position is open to graduate students on a PhD track only, and the length of the internship is three months with the possibility of extending if required. The intern is expected to disseminate this research in top tier scientific conferences such as RSS, IROS, ICRA etc., and if applicable, help with filing associated patents. Start and end dates are flexible.

    • Research Areas: Artificial Intelligence, Machine Learning, Robotics
    • Host: Radu Corcodel
    • Apply Now
  • CV1925: Symmetries, equivariance and invariance in deep learning

    • MERL is seeking an intern to conduct research in the areas of learning symmetries from data and equivariant neural networks for applications in computer vision. The ideal candidate is a PhD student with experience in deep learning and computer vision and a good publication record at top-tier venues. Prior knowledge and experience with group theory/geometry and equivariant neural networks are a big plus. 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.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Suhas Lohit
    • Apply Now
  • CV1920: Conditional Diffusion Models in Computer Vision

    • We seek a highly motivated intern to conduct original research in conditional diffusion models for computer vision tasks. We are interested in applications to various tasks including image editing, multimodal generation, and image-to-image translation. 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 (or postdoc) in computer vision and machine learning with a strong publication record. 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. Previous experience in diffusion models is required.

    • Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    • Host: Tim Marks
    • Apply Now