Deploying reinforcement learning algorithms within LUCID’s neuro-biometric IPE (Individualized Psychoacoustic Entrainment) system - ON-155
Preferred Disciplines: Machine Learning, Computer Science, Mathematics (Masters, PhD or Post-Doc)
Company: Lucid Inc.
Project Length: 12-18 months (3 units)
Desired start date: As soon as possible
Location: Toronto, ON
No. of Positions: 1
Preferences: Ryerson University is certainly preferred but any Greater Toronto Area school could work as well
About the Company:
LUCID creates immersive music experiences that use neuro-biometrics and AI to give people more control of their mental wellness. Our vision is to combine art, science and technology to promote accessibility, empathy and creativity in the mental health discourse and to find real solutions for our society’s wellness needs.
LUCID has developed a proprietary process that provides users with individualized psychoacoustic entrainment seamlessly embedded within music, capable of inducing meditative and therapeutic mental states. Our system currently reads the neuro-biometric signals of a user, feeds that data through an automated decision tree system that then alters various psychoacoustic elements of a soundtrack in order to provide the necessary psychoacoustic entrainment, catered to the unique needs of each user. This process effectively creates a full feedback loop, with the user controlling the stimulus, and the stimulus inducing the user. It is our hypothesis that with the proper training, our system could be capable of acting on the brain’s neuroplastic capabilities, potentially acting as a treatment methodology for various psychological challenges. With this research project, it is our plan to infuse machine learning algorithms within our system in order to develop a network effect, with the system becoming exponentially more efficient with the continuous use of our technology. As our company plans to commercialize and conduct large-scale studies, this integration will provide us with the opportunity to get the most out of these user experiences and continue pushing the boundaries necessary to execute our company’s vision.
- Deploy reinforcement algorithms within LUCID’s core system
- Integrate these algorithms cross-platform (Android, iOS, Mac, Windows)
- Establish a cloud-based platform to enable machine learning across all LUCID environments (mobile & PC)
- To be determined
Expertise and Skills Needed:
- Advanced programming/mathematics
- Proficiency with Machine learning/AI
- Knowledge of cloud computing/big data
- Proficiency with multiple platforms (Android, iOS, Mac, Windows)
- Knowledge of the Unity programming environment is an asset but not required
For more info or to apply to this applied research position, please