Internship - Neural Spatial Audio Processing

Internship - Neural Spatial Audio Processing

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. The ideal candidates are senior Ph.D. students with experience in some of the following: microphone array processing, physics informed machine learning, and 3D modeling in computer vision. Multiple positions are available with flexible start date (not just Spring/Summer but throughout 2026) and duration (typically 3-6 months).

Required Specific Experience

• Experience with deep learning frameworks (e.g., PyTorch and JAX)
• Research experience in spatial audio and/or array signal processing