Artificial Intelligence is the next big player in Genomics and your career.
Are you a graduate student or a recent graduate with experience in Genomics and interested in Artificial Intelligence?
What you gain from the program
Capability to read a Machine Learning Genome paper and understand it
Know the standard structures of data to be used with Machine Learning tools
Methodologies to discover and validate problems
Propose a potential application of Machine Learning within a Genomics Project
Basic understanding of Human-AI Interaction
Ethics of AI
Working as a team to develop ML solutions & cash prizes for top three projects
12 Week Journey
Current areas of interest
ML Boot camp
How can AI be used in LS
Accessing data quality
Different data modalities
Need validation Human AI Interaction ethically designed
Work with Genome Project to make sense of data and gather insights.
Demo of projects
Networking with ecosystem players
Sydney Swaine Simon
AI District Fellow and Cofounder of Neurotech X.
Life Sciences Fellow
Joseph Paul Cohen
Program Scientific Advisor, Postdoctoral Fellow, Mila, University of Montreal
Postdoctoral Research Scientist at Montreal Heart Institute and Mila
PhD student, Mila, University of Montreal
IVADO assistant professor, Faculty of Medicine, Université de Montréal
AI District Fellow Assistant
Frequently Asked Questions.
Who is eligible?
Once accepted, how long will the program last?
Start: January 20th
Do I need to be part of Concordia University to get access to District 3’s services?
Our services are open to all individuals who are looking to discover innovation and entrepreneurship.
Does District 3 charge fees, take equity or claim intellectual property?
Your intellectual property remains your own, and we don’t take equity or charge any fees.
How many hours per week is the program?
You must be capable to commit to 15 hours/week, 3 hours of workshops and 12 hours additional work per week.