Internship - Neural Spatial Audio Processing

About the role

We are seeking graduate students interested in advancing the fields of spatial audio, room acoustics, physics-informed machine learning, and scene understanding (e.g., sound source localization and spatial-aware captioning). The interns will work closely with MERL researchers to develop novel algorithms, record data, conduct experiments, and prepare results for publication. Internships regularly lead to one or more publications in top-tier venues, which can later become part of the intern's doctoral work.

Responsibilities

• Develop novel algorithms in spatial audio, room acoustics, or physics-informed machine learning
• Record data and conduct experiments
• Prepare results for publication in top-tier venues

Requirements

• Senior Ph.D. student status
• Experience with deep learning frameworks (e.g., PyTorch and JAX)
• Research experience in spatial audio and/or array signal processing
• Full authorization to work in the U.S. and ability to comply with governmental access control restrictions for technology and information

Qualifications

The ideal candidates will have experience in some of the following:

• Microphone array processing
• Physics-informed machine learning
• 3D modeling in computer vision

Schedule

• Multiple positions available with flexible start dates throughout 2026
• Duration: typically 3-6 months

Pay

The pay range for this internship position is $6,000–$8,000 per month.

Benefits

• Relocation stipend
• Covered travel to and from MERL
• Monthly Charlie Card for local commuting
• Weekly social gatherings and professional development opportunities, including research talks by internal and external speakers
• Health insurance coverage after a 90-day waiting period
• Immigration support for qualified candidates as needed