Faculty/Division: Faculty of Arts & Science
Department: Computer Science
Campus: St. George (Downtown Toronto)
Supervisors: Prof. Chris Maddison and Prof. Matthieu Schapira
Overview
A postdoctoral position is available immediately under the co-supervision of Prof. Chris Maddison and Prof. Matthieu Schapira at the University of Toronto. The successful candidate will work at the intersection of artificial intelligence and drug discovery, with a focus on developing and applying machine learning methods to predict small molecule binders for challenging protein targets. This project is part of a collaboration between the Department of Computer Science and the Structural Genomics Consortium (SGC) at the University of Toronto.
The postdoc will have the opportunity to contribute to two major initiatives:
1. The Critical Assessment of Computational Hit-finding Experiments (CACHE) challenges, a series of prospective benchmarking exercises to evaluate progress in computational hit-finding. An overview of the challenge was recently released (Li et al., 2024).
2. Machine learning on DNA-encoded library (DEL) data and Affinity Selection Mass Spectrometry (ASMS) data for hit discovery, leveraging the SGC's ongoing, large-scale data collection efforts.
The successful candidate will join a vibrant multi-disciplinary research environment, collaborating with computer scientists, structural biologists, chemists, and drug discovery experts.
Desired Experience:
- PhD obtained within the last 2 years in computer science, computational chemistry, bioinformatics, or a related field.
- A strong background in machine learning (ML) is required, with a particular expertise in generative models, search algorithms, and/or deep learning for molecular property prediction.
- Proficiency in Python and relevant ML libraries (e.g., PyTorch, TensorFlow).
- Familiarity with high-performance computing environments.
- Basic knowledge of structural biology, medicinal chemistry, and drug discovery principles is an asset.
- Experience with computational chemistry tools and concepts, such as molecular docking, cheminformatics, and QSAR modeling is an asset.
- Strong interpersonal skills and exceptional motivation for contributing to collaborative cutting-edge research.
The successful candidate will have the opportunity work with an international community of computational and medicinal chemists. They will also contribute to the development of novel ML approaches for hit discovery.
Interested candidates, please send a CV, cover letter, and contact information for three references to hrsgctoronto@thesgc.org with the subject line 'Postdoctoral Position in AI for Drug Discovery'.
Interested candidates are should also apply for a Vector Institute Postdoctoral Fellowship, to enhance their training and marketability in today’s interdisciplinary workforce.
About us:
The Department of Computer Science at the University of Toronto is a global leader in computer science research and education. Located in the heart of Toronto, the department offers a vibrant research environment with strengths in artificial intelligence, machine learning, and computational biology.
The Structural Genomics Consortium (SGC) is a global public-private partnership dedicated to open science that accelerates the discovery of new medicines. The SGC has approximately 200 scientists across seven major research sites, with the largest site located at the University of Toronto. The SGC-Toronto lab resides within the University of Toronto's Temerty Faculty of Medicine and has extensive expertise in structural biology, chemical biology, and drug discovery.
FTE:100%. The normal hours of work are 40 hours per week for a full-time postdoctoral fellow (pro-rated for those holding a partial appointment) recognizing that the needs of the employee's research and training and the needs of the supervisor's research program may require flexibility in the performance of the employee's duties and hours of work. Employment as a Postdoctoral Fellow at the University of Toronto is covered by the terms of the CUPE 3902 Unit 5 Collective Agreement.
Diversity Statement:
The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
Accessibility Statement:
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission. The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodation as required for applicants with disabilities. If you require any accommodation at any point during the application and hiring process, please contact hrsgctoronto@thesgc.org.