Internship Openings

2 / 17 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.

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Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.


  • ST0096: Internship - Multimodal Tracking and Imaging

    • MERL is seeking a motivated intern to assist in developing hardware and algorithms for multimodal imaging applications. The project involves integration of radar, camera, and depth sensors in a variety of sensing scenarios. The ideal candidate should have experience with FMCW radar and/or depth sensing, and be fluent in Python and scripting methods. Familiarity with optical tracking of humans and experience with hardware prototyping is desired. Good knowledge of computational imaging and/or radar imaging methods is a plus.

      Required Specific Experience

      • Experience with Python and Python Deep Learning Frameworks.
      • Experience with FMCW radar and/or Depth Sensors.

    • Research Areas: Computer Vision, Machine Learning, Signal Processing, Computational Sensing
    • Host: Petros Boufounos
    • Apply Now

  • ST0174: Internship - Sensor Reasoning Models

    • The Computation Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research on sensor reasoning models—algorithms that can understand, explain, and act on multi-sensor data (e.g., RF, infrared, LiDAR, event camera) through text-, visual-, and multimodal reasoning. Ideal candidates will be comfortable bridging modern perception (detection/segmentation/tracking) with higher-level reasoning capabilities. Experience with text, visual, and multimodal reasoning is highly preferred. The intern will work closely with MERL researchers to develop novel algorithms, design experiments using MERL’s in-house testbeds, and prepare results for patents and publication. The internship is expected to last 3 months, with a flexible start date from October 2025 onward.

      Required Specific Experience

      • Reasoning with sensor data: Demonstrated work in text-, visual-, and multimodal reasoning (e.g., VQA over sensor streams, temporal/spatio-temporal reasoning, chain-of-thought, instruction following).
      • LLMs & VLMs for sensor perception: Experience aligning or conditioning LLMs/VLMs on sensor outputs (e.g., point clouds, radar heatmaps, BEV features).
      • Perception foundations: Solid understanding of state-of-the-art transformer-based (e.g., DETR) and diffusion-based (e.g., DiffusionDet) frameworks
      • Datasets & evaluation: Hands-on experience with open large-scale multi-sensor datasets (e.g., nuScenes, Waymo Open Dataset, Argoverse) and open radar datasets (e.g., MMVR, HIBER, RT-Pose, K-Radar). Ability to design reasoning-centric benchmarks (e.g., QA over multi-sensor inputs, temporal prediction).
      • Proficiency in Python and deep learning frameworks (PyTorch/JAX), plus experience with GPU cluster job scheduling and scalable data pipelines.
      • Proven publication record in top-tier venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML (or equivalent).
      • Knowledge of sensor (RF, infrared, LiDAR, event camera) fundamentals; for radar, familiarity with FMCW, MIMO, Doppler signatures, radar point clouds/heatmaps, and raw ADC waveforms.
      • Familiarity with MERL’s recent radar perception research, e.g., TempoRadar, SIRA, MMVR, RETR.

    • Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning
    • Host: Perry Wang
    • Apply Now