Discovery Scientist, Protein Designer
Job Summary
Join our research lab in Toronto focused on applying machine learning to longevity research. We are developing ML-based pipelines for efficient exploration of chemical space and discovering anti-aging interventions, with a focus on cellular senescence and cryoprotectants. 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
We are currently seeking 1-2 Machine Learning Postdocs, a Molecular Biology Lab Technician, and a Chemistry Postdoc. Additionally, we are looking for students enrolled in January at the University of Toronto. For more details and to forward this opportunity, please contact us.
Responsibilities
- Develop and optimize machine learning pipelines for chemical space exploration
- Collaborate with experts in cellular senescence and chemistry
- Contribute to the discovery of novel cryoprotectants and anti-aging interventions
- Work on synthesis of molecule candidates and parallel synthesis using self-driving labs
Requirements
- Strong background in machine learning and computational chemistry
- Experience with generative models and active learning
- Interest in longevity research and aging-related fields
- Ability to work in an interdisciplinary team
Qualifications
- PhD in relevant field
- Relevant postdoctoral experience
- Strong publication record
Skills
- Machine learning
- Computational chemistry
- Collaboration and teamwork
- Problem-solving skills
Benefits
- Competitive salary
- Flexible working hours
- Opportunities for professional growth and mentorship
Pay
Competitive salary based on experience and qualifications
Schedule
Full-time position with flexible working hours
Contact
To apply, please forward this opportunity to interested individuals. For further inquiries, reach out via email or the provided link.