Description: This postdoctoral research position is available for a highly motivated candidate to study bio-acoustic signals such as voice, speech and respiratory sounds using machine learning and data visualization methods. The individual selected for this position will be working on a large-scale NIH funded project from the Bridge2AI program funded through the Common Fund. The Bride2AI-Voice project aims to integrate the use of voice as biomarker of health in clinical care by generating a substantial multi-institutional, ethically sourced, and diverse voice database linked to multimodal health biomarkers to fuel voice AI research and build predictive models to assist in screening, diagnosis, and treatment of a broad range of diseases.
It is expected that candidate’s professional background will allow them to contribute to research related to developing and evaluating AI/ML methods for acoustic signal processing and data visualization. Data presentation and participation at laboratory meetings, seminars, and conferences are expected, as are participation in the preparation of research materials for manuscript and grant submissions. Must have demonstrated the ability to design and execute experiments and acquire, analyze, and interpret the data