Audio R&D Scientist – Machine Learning & DSP

New York, NY     ·   Virtual

The Audio R&D Scientist is responsible for developing machine learning and audio signal processing algorithms for analyzing and converting EEG data from imagined sound into digital audio synthesis.

The position involves addressing specific challenges related to audio signal processing and optimization/machine learning that require in-depth experimentation and understanding. It involves surveying the literature, setting up test environments in MATLAB, participate in data collection, carrying out analysis of audio data, and developing algorithms on MATLAB and Python. The ideal candidate will have a strong understanding of neuroscience and EEG signal processing, machine learning and wearable brain-computer interfaces

Responsibilities:

• Participate in the design and evaluation of machine learning and signal processing algorithms
• Characterize audio signals using FFT, spectrograms, transient separation, formant analysis, envelope extraction, etc.
• Implement feature extraction and audio processing algorithms based on DSP/ML in MATLAB/Python/JUCE, considering real-time and embedded systems implementation requirements
• Summarize, document, and communicate findings, solutions, and strategies
• Participate in acoustical measurements, data collection, develop experiment protocols, organize user studies