Multimodal Emotional Data Collection

Description

We are  seeking a highly motivated Master's student to contribute to an innovative research project aimed at better understanding the physiological and emotional responses associated with sound-induced distress in individuals with decreased sound tolerance (DST). DST can significantly affect quality of life, leading to discomfort, distress, and avoidance of everyday listening environments. This project aims to develop a multimodal data collection framework to characterize the physiological, behavioral, and subjective responses associated with sound-induced distress. Using wearable technologies, including hearables and other physiological sensors, the student will participate in the design and implementation of a study involving individuals with DST. The project will be co-supervised by Prof. Rachel E. Bouserhal (ÉTS) and Prof. Sylvie Hébert (UdeM) and involves interdisciplinary collaboration among researchers in engineering, audiology, and health sciences. 

The student will join the Research in Hearing, Health, and Assistive Devices (RHAD) Lab, directed by Prof. Rachel E. Bouserhal at ÉTS. The laboratory develops advanced signal processing and machine learning algorithms for health monitoring applications using signals captured from wearable devices, with a particular focus on hearables and other unobtrusive sensing technologies. The selected candidate will benefit from a collaborative and multidisciplinary research environment and will work closely with academic, clinical, and community partners. 

Responsibilities

• Designing experimental protocols and data collection procedures;
• Recruiting and coordinating research participants;
• Collecting physiological and self-reported data;
• Processing and analyzing biomedical signals;
• Developing algorithms for multimodal data analysis;
• Contributing to scientific publications and conference presentations.
   

How to Apply

Interested candidates are requested to submit their applications, including a CV, academic transcripts, contact information of two references, and a cover letter explaining their interest in the position and their relevant skills to Prof. Rachel Bouserhal. We encourage all qualified candidates to apply, regardless of origin, gender, sexual orientation or disability status. We are committed to diversity and inclusion in our team.