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Postdoctoral Researcher

University Health Network

Toronto, ON

Job typeFull-time
SpecialtyTechnical
Compensation$54,902 – $93,333/year
PostedJun 3, 2026

🔒 Application Instructions

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LocationCollege Street, Toronto, ON, CAOpen

eHealth role summary

Develops ML/AI models and performs data engineering for drug discovery, cheminformatics and computational biology (bioinformatics), which falls under health-related computational biology/health data science.

About this role

Union: Non-Union
Number of Vacancies: 1
New or Replacement Position: New
Site: MaRS
Department: Structural Genomics Consortium
Reports to: Senior Scientist
Salary Range: $54,902 - $93,333 Per Year 
Hours: 37.5 Hours Per Week
Shifts: Monday - Friday; Day Shifts
Status: Temporary Full-time (2-Year Contract)
Closing Date: June 19, 2026

Position Summary:
We seek a Data scientist to develop innovative machine learning (ML) and Artificial Intelligence (AI) methods to predict drug-like small molecules from large chemical screens based on the DNA Encoded Library (DEL) and Affinity Selection Mass Spectrometry (ASMS) technologies. 

The candidate will be hosted by the Structural Genomics Consortium (SGC), Haibe-Kains and Schapira labs. The candidate will be responsible for aggregating the existing and future drug screening data and developing novel integrative machine learning/AI models for the identification of potential drug targets; approved or experimental drugs.

The candidate will be assisted by software developers to leverage internal tools (AIRCHECK) in order to develop, train and test ML and DL predictive models, independently or in collaboration with other experts in the Haibe-Kains and Schapira labs and other SGC collaborators. 

Duties:

  • Develop and implement novel ML/AI algorithms to predict drug-like small molecules from large-scale chemical screening datasets.
  • Utilize computational approaches to analyze complex drug screening data and extract meaningful insights.
  • Collaborate with computational biologists and software developers to build, validate predictions and deploy models on the AIRCHECK platform.
  • Contribute to the design and execution of experiments to validate target predictions.
  • Stay abreast of the latest advancements in machine learning, AI, and chemical biology research.
  • Publish research findings in high-impact scientific journals and present results at conferences.

 

Qualifications

  • Awarded a PhD within the previous 5 years, or an MD or DDS within the previous 10 years, in computational chemistry, computer science, engineering, applied physics or equivalent. 
  • Strong background in AI, deep learning, and machine learning.
  • Published/submitted papers in Scientific Journals or Conference Proceedings.
  • Experience with analysis of high-throughput drug screening data, such as DNA-Encoded Library (DEL) and/or Affinity Selection Mass Spectrometry (ASMS).
  • Strong data engineering skills.
  • Strong expertise in programming and machine learning (eg, PyTorch, VertexAI, Flask, TensorFlow).
  • Excellent communication skills and ability to work effectively in a collaborative research environment.
  • Prior experience in computational chemistry or drug discovery research, preferred
  • Knowledge of cheminformatics, structural bioinformatics, or systems biology, preferred
  • Experience with high-performance computing and cloud computing platforms like Google Cloud Platform, preferred

Additional Information

Why join UHN?
In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

  • Competitive offer packages
  • Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
  • Close access to Transit and UHN shuttle service
  • A flexible work environment
  • Opportunities for development and promotions within a large organization
  • Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.