Scientist in Molecular Engineering by Machine Learning
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.
Applicants must have a PhD, MD, or MD/PhD or equivalent in a relevant discipline and a record of scientific accomplishments in the aforementioned research areas. Salary will be commensurate with qualifications and experience. A competitive benefits package will be offered along with support for relocation expenses.
Interested individuals should email their application comprised of a curriculum vitae, a description of past research (maximum 1 page), a detailed proposed research program (maximum 4 pages), and copies of main research publications in PDF format to the Co-Chairs, Molecular Engineering by Machine Learning Search Committee at firstname.lastname@example.org by November 7, 2023. Applicants must also arrange to have three signed letters of reference on institutional letter head sent directly to the Search Committee Chairs at email@example.com, indicating the applicant’s name in the subject line, also by November 7, 2023. Late applications may be reviewed, but priority will be given to those submitted by the closing date. The search committee will interview applicants beginning in late 2023, with a potential start date in summer or fall 2024.
SickKids believes that diversity positively impacts science and is essential to sustain our vibrant world-leading research community. SickKids welcomes applications from racialized persons / persons of colour, women, Indigenous Peoples, persons with disabilities, 2SLGBTQIA+ persons, and others who contribute to the further diversification of ideas. Informed by the Accessibility for Ontarians with Disabilities Act (AODA), the Ontario Human Rights Code, and our Access and Accommodation Policy, SickKids is proud to make accommodations to support applicants during the interview and assessment process, if requested. Please advise the SickKids Research Institute Faculty Development & Diversity Office at firstname.lastname@example.org of your accessibility needs during the recruitment process. Information received relating to accommodation will be addressed confidentially. As part of the application process, you will be asked to complete a brief voluntary diversity survey. Any information directly related to you is confidential and cannot be accessed by either the search committee or human resources staff. Results will be aggregated for institutional planning purposes. The self-identification information is collected, used, disclosed, retained and disposed of in accordance with the Privacy Act and the Access to Information Act.
SickKids recognizes that scholars have varying career paths and that career interruptions can be part of an excellent academic record. Candidates are encouraged to share any personal circumstances in order to allow for a fair assessment of their application.
All qualified applicants are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadians and permanent residents will be given priority. The successful candidate will hold an appropriate and valid work permit, if applicable. Only those applicants selected for the interview will be contacted. Wherein a practicing MD, the successful candidate must hold or be eligible for licensure with the College of Physicians and Surgeons of Ontario.
Applicants may direct any informal inquiries to:
Co-Chairs, Molecular Engineering by Machine Learning Search Committee
SickKids Research Institute - The Peter Gilgan Centre for Research & Learning
686 Bay Street Toronto, Ontario Canada M5G 0A4