Scientist in Molecular Engineering by Machine Learning

Overview

The Hospital for Sick Children (SickKids) Research Institute seeks an outstanding scientist whose research is focused on the development and utilization of computational machine learning approaches for the design and engineering of biomolecules. Designed molecular biologics – including antibodies, nanobodies, miniproteins, vaccines, enzymes, toxins, peptides, and nucleic acids – are poised to revolutionize biomedical research and therapeutic discovery. This permanent position lies at the interface between computational design, structural biology, and therapeutic development, and aligns with our SickKids Precision Child Health strategic initiative. 

The successful candidate will be appointed as a Scientist in the Molecular Medicine research program at the SickKids Research Institute. SickKids is a world-renowned paediatric hospital with seven fully integrated research programs. The successful applicant’s laboratory will be located in the state-of-the-art Peter Gilgan Centre for Research & Learning (686 Bay Street, Toronto, Canada), in the Discovery District of the heart of downtown Toronto. This unique environment for biomedical science sits in close proximity to nine other academic hospital research centres and the University of Toronto campus.

The successful applicant will initiate and maintain an original, competitive, and independently funded research program of international caliber in the area of biomolecular design using machine learning in conjunction with experimental approaches including functional assays, structure determination, biophysical characterization and/or directed evolution. Designed biologics would be applied as probes of biological function and/or candidate therapeutic leads across the breadth of paediatric medicine. The successful candidate will benefit from the extensive research and core facilities of SickKids, the University of Toronto and its affiliated institutions for structural biology, biophysics, drug discovery, cellular imaging, functional genomics, proteomics, metabolomics, bioinformatics, computational biology, machine learning, and artificial intelligence, as well as new inter-institutional initiatives focused on biologics and therapeutic design.

The successful applicant is expected to qualify for an academic status-only appointment in an appropriate department at the University of Toronto, Canada’s largest university and a world leader in machine learning. The successful candidate will also be considered by the Vector Institute for appointment as a Faculty Member or Faculty Affiliate. Vector is home to over 700 active researchers with broad expertise in artificial intelligence, including Faculty Members, Faculty Affiliates, and trainees in a world-class machine learning research environment. Vector is supported by government and private industry, in partnership with Ontario universities. Faculty that are co-recruited with Vector benefit from access to high performance computing capacity and resources for cutting edge artificial intelligence and machine learning research at Vector.