Internship - Multi-Modal Sensing and Understanding

About the role

The Computational Sensing team at MERL is seeking a highly motivated intern to conduct fundamental research on multi-modal sensing and understanding algorithms that can understand, explain, and act on multi-sensor data (e.g., RF, infrared, LiDAR, event camera). Ideal candidates will be comfortable bridging state-of-the-art perception (detection/segmentation/tracking) with higher-level semantic understanding and reasoning capabilities. Experience with text, visual, and multimodal reasoning is a plus.

Responsibilities

- Work closely with MERL researchers to develop novel algorithms. - Design experiments using MERL’s in-house testbeds. - Prepare results for patents and publication.

Requirements

- Expertise in physical sensing across RF (radar, UWB, Wi-Fi), infrared, LiDAR, and event-camera modalities. Experienced with radar systems and concepts including FMCW and MIMO configurations, Doppler signature interpretation, radar point cloud and heatmap representations, and raw ADC waveforms. - Solid understanding of state-of-the-art transformer-based (e.g., DETR) and diffusion-based (e.g., DiffusionDet) frameworks. - Demonstrated work in text-, visual-, and multimodal semantic understanding and reasoning. - 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). - 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).

Qualifications

- Bachelor's degree in Computer Science, Electrical Engineering, Physics, or a related field. - Relevant coursework or projects in computer vision, machine learning, and sensor fusion. - Strong programming skills in Python and proficiency with deep learning frameworks. - Ability to work independently and collaboratively in a fast-paced research environment.

Skills

- Expertise in physical sensing across RF, infrared, LiDAR, and event-camera modalities. - Solid understanding of state-of-the-art transformer-based and diffusion-based frameworks. - Demonstrated work in text-, visual-, and multimodal semantic understanding and reasoning. - Hands-on experience with open large-scale multi-sensor datasets and open radar datasets. - Proficiency in Python and deep learning frameworks (PyTorch/JAX). - Experience with GPU cluster job scheduling and scalable data pipelines. - Proven publication record in top-tier venues.

Benefits

- Relocation stipend. - Covered travel to and from MERL. - Monthly Charlie Card for local commuting. - Weekly social gatherings and professional development opportunities. - Eligibility for health insurance coverage after a 90-day waiting period. - Immigration support for qualified candidates.

Pay

The pay range for this internship position will be 6-8K per month.