JOB POSTING INFORMATION
Position Type:	Professional Experience Year Co-op (PEY Co-op: 12-16 months)
Job Title:	Research Intern (PEY) - Machine Learning: Internship Opportunities
Job Location:	Toronto, ON
Job Location Type:	Hybrid - 2 days in office
If working on site, can you provide a copy of your COVID-19 safety protocols?:	Yes
Number of Positions:	1
Salary:	Salary Not Available, 40.0 hours per week
Start Date:	05/06/2024
End Date:	05/30/2025
Job Function:	Engineering
Job Description:	About Us Deep Genomics is a startup that is working to revolutionize drug development by decoding RNA biology using artificial intelligence (AI). Our proprietary platform, the AI Workbench, enables us to find novel gene targets critical to disease and design drug molecules to target them. This platform has already produced several antisense oligonucleotide drugs that we are advancing toward clinical application. Founded in 2015 by Brendan Frey, a pre-eminent AI researcher from the University of Toronto, our company has expanded well beyond its AI research-focused origins. We have grown to encompass an extensive wetlab biology team for testing and validating the drugs we create using our models. We have built a tight feedback loop between the dry-lab and wet-lab parts of the company, allowing us to rapidly validate the molecules our AI platform produces, while also generating data to refine the next generation of our models. Deep Genomics is based in Toronto, and has additional locations in Boston and Montreal. We embrace a hybrid work style that allows our scientists to benefit from the best aspects of both in-person and remote work. Where you fit In We are seeking upper-year undergraduate students for a 12- to 16-month full-time internship in 2024 to join our Machine Learning (ML) team. In this role, you will collaborate with leading scientists working at the intersection of ML and genomics to develop novel drugs for previously untreatable diseases. We are building our state-of-the-art AI Workbench, encompassing groundbreaking models such as the recently published BigRNA, and using it to identify novel gene targets implicated in disease and design drug molecules to modulate them. Collaboration across disciplines is critical to our team’s success, such that team members are routinely working alongside molecular biologists, data scientists, software engineers, and medical researchers. As part of this team, you will help build models that are rapidly deployed for production use as part of our drug development pipeline, and which are published for use by the wider scientific community. What you will do: - Develop and evaluate models of genomics, cell biology, and drug-target interactions using state-of-the-art deep learning techniques, building on both public and proprietary datasets. - Help build software for training, debugging, and deploying predictors. - Work closely with computational and wetlab biology scientists to use these models to design drugs. - Help design new wetlab experiments that will validate the models and produce data to refine them. What We Offer:  - Inspiring, creative and fast-moving startup located right next to the University of Toronto and within the MaRS Discovery District – an expanding hub of research in AI and genomics - Exceptional opportunity to work alongside a bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology - Competitive compensation package
Job Requirements:	What you bring: - Currently enrolled in an undergraduate program in Computer Science, Electrical Engineering, Engineering Science, Mechanical Engineering, Math and Stats, or a related discipline. - Must be eligible to participate in a 12-16 months full time internship/co-op program. - Experience with designing, training, debugging and evaluating neural networks using modern frameworks such as PyTorch, JAX, etc. - Some background in molecular biology and genomics is helpful but not necessary. We offer extensive tutelage in these subjects, and many past interns have been extremely successful even without this background. - Excellent scientific writing and presentation skills. You will have the opportunity to present your work to and seek feedback from audiences originating from diverse backgrounds, providing invaluable experience in presenting highly technical ML-focused work to non-ML-specialist audiences. - Strong organizational, interpersonal, and communication skills.
Preferred Disciplines:	Computer Engineering Computer Science Electrical Engineering Engineering Science (Biomedical) Engineering Science (Electrical and Computer) Engineering Science (Machine Intelligence) Engineering Science (Math, Stats & Finance) Engineering Science (Nanoengineering) Engineering Science (Physics) Engineering Science (Robotics) Mechanical Engineering Math & Stats
All Co-op programs:	No
Targeted Co-op Programs:	Targeted Programs Professional Experience Year Co-op (12 - 16 months)

APPLICATION INFORMATION
Application Deadline:	Feb 29, 2024 11:59 PM
Application Receipt Procedure:	Employer Website
If by Website, go to:	https://jobs.lever.co/deepgenomics/26bc69b9-0225-4a25-9f51-0cc3116d55b4
Additional Application Information:	Deep Genomics thanks all applicants, however only those selected for an interview will be contacted.  Deep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. NOTE from the Engineering Career Centre In addition to your application by email/website, please ensure that you select the “I intend to apply for this position” tab on the portal.  This will give us a record of your submitted application in the event that you are invited for interviews.
U of T Job Coordinator:	Nabeela Rahman

ORGANIZATION INFORMATION
Organization:	Deep Genomics
Division:	Predictive Systems
Website:	www.deepgenomics.com

ADDITIONAL INFORMATION
Length of Workterm:	FLEXIBLE PEY Co-op: 12-16 months (range)