Internship, Science Operations
Job Summary
Looking for mission-aligned individuals to join my research lab in Toronto. Our group focuses on developing machine learning-based pipelines for the efficient exploration of chemical space, with applications to the discovery of anti-aging interventions, particularly in cellular senescence and cryoprotectant discovery. Collaborations span across The Hospital for Sick Children, University of Toronto, and Vector Institute, with strong ties to industry through ongoing collaborations with Genentech.
About the Role
The lab is part of a multidisciplinary team including machine learning, molecular biology, and chemistry. We are seeking 1-2 machine learning postdocs, a molecular biology lab technician, and a chemistry postdoc. Additionally, we are open to recruiting students starting in January at the University of Toronto.
Responsibilities
- Develop machine learning-based pipelines for chemical space exploration
- Collaborate with experts in cellular senescence and chemistry
- Work on the synthesis of molecule candidates and parallel synthesis
- Explore possibilities of spinning off current projects
Requirements
- Strong background in machine learning
- Experience in molecular biology and/or chemistry
- Ability to work in a multidisciplinary environment
Qualifications
- PhD in Machine Learning, Molecular Biology, or Chemistry
- Research experience in relevant areas
Skills
- Machine learning
- Molecular biology
- Chemistry
Benefits
- Opportunities for interdisciplinary collaboration
- Strong collaborative environment with leading institutions
- Industry connections through ongoing collaborations
Pay
Competitive salary based on experience and qualifications
Schedule
Full-time position with flexible working hours
Contact
Please forward this opportunity to anyone interested. For inquiries, please contact us here or email directly.