Information Retrieval from Unstructured Medical Content-ON-531

Project type: Research
Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences, Mathematics, Operations research
Company: Tali AI
Project Length: 6 months to 1 year
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Toronto, ON, Canada; Canada
No. of positions: 2
Desired education level: PhDPostdoctoral fellow
Open to applicants registered at an institution outside of Canada: Yes

About the company: 

Tali is a seed stage startup, we have partnered with the largest operator of clinics in Canada to provide Tali as a point of care support tool to physicians. 
Physicians can ask their question in natural language and get their answer back from thousands of pages of medical content.

Describe the project.: 

Tali is an information retrieval engine from unstructured medical content. We are an NLP first company. We integrate with Electronic Medical Record software of physicians and provide an interface where physicians can ask their question in natural language and get their answer back. Tali is voice-enabled so a component of what we are trying to build for Tali is a voice to text engine specialized to work on medical content and very high accuracy because the time crunch physicians are under, at the point of care.

The project aims to research and apply NLP algorithms on voice to text and information retrieval on medical content,  using a combination of classic and modern NLP algorithms alongside deep learning methods.

Required expertise/skills: 

Natural Language Process, Machine Learning