Multimodal Sensing Intern: Radar, LiDAR & AI Research

merl; Cambridge (MA); On-site; USD 67,000 - 89,000; Full time

Benefits offered by this job

Relocation stipend

Travel to MERL covered

Charlie Card for local commuting

Weekly research talks and professional

Health insurance after 90-day waiting

Job summary

MERL's Computational Sensing team 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 bridge state-of-the-art perception with higher-level semantic understanding and reasoning, contribute to experiments using MERL’s testbeds, and work toward results suitable for patents and publication.

Qualifications

• Experience with RF, infrared, LiDAR, and event-camera data.
• Experience with transformer-based and diffusion-based frameworks.
• Text, visual, and multimodal semantic understanding experience.
• Experience with open large-scale multi-sensor datasets (e.g., nuScenes, Waymo).
• Proficiency in Python and deep learning frameworks (PyTorch/JAX); GPU clustering and data pipelines.
• Proven publication record in top venues.

Responsibilities

• Conduct fundamental research on multi-modal sensing algorithms.
• Bridge perception with semantic understanding and reasoning.
• Design experiments using MERL’s in-house testbeds and develop novel approaches.
• Prepare results for patents and publication.

Skills

Multimodal sensing

Python

Deep learning

Transformer models

Research publications

Multimodal reasoning

Tools

PyTorch

JAX

CUDA

GPU clusters

Job description

MERL's Computational Sensing team 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 bridge state-of-the-art perception with higher-level semantic understanding and reasoning, contribute to experiments using MERL’s testbeds, and work toward results suitable for patents and publication.