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Current Opportunities

Postdoctoral Fellow, Computational Chemistry & Chemoinformatics - Toronto, Ontario

Position: Postdoctoral Fellow, Computational Chemistry & Chemoinformatics
Site: MaRS Centre, Toronto
Department: Drug Discovery Program
Reports To: Dr. Gennady Poda, PhD, Scientific Advisor
Salary: Commensurate with level of experience
Hours: 35 hours/week
Status: Full-time, Temporary (Two-years with potential one-year extension)

The Drug Discovery Program at the Ontario Institute for Cancer Research (OICR) is seeking a post-doctoral scientist with expertise in Computational Chemistry and Chemoinformatics.

The OICR Drug Discovery Program is one of the largest programs of its kind in Canada. Our mission is to help efficiently translate discoveries made in Ontario’s labs into novel oncology therapies. Based in Toronto, you will be a part of a dedicated team of scientists to identify and optimize new anti-cancer drug candidates using a wide variety of computational approaches. As a member of the Drug Discovery Program, you will have a chance to use the state-of-the-art OICR hardware facilities (that includes a 14,000-core SGE HPC Cluster with 16 PB data storage), Drug Discovery servers and all major commercial software tools required for Computational Drug Discovery, which is currently used by pharmaceutical companies. You will closely collaborate with a team of scientists with a broad Pharma and Biotech experience in the fields of Computational Chemistry, Chemoinformatics, Medicinal Chemistry, Biochemistry, Cell and in vivo Biology and DMPK and contribute to several anti-cancer drug discovery projects. As a part of collaborative projects, you will also interact with leading academic scientists and physicians in Toronto’s Discovery District, including a recently funded grant from COVID-19 Ontario Rapid Research Fund to identify new therapeutics and existing drugs that could be repurposed for the treatment of COVID-19 (bit.ly/2PtqEBr).

To find out more about what’s happening in Drug Discovery, visit OICR News.


  • Collaborate effectively with Medicinal Chemists in the group and contribute to drug discovery projects via a wide variety of Molecular Modeling, Chemoinformatics, Ligand- and Structure-Based Analog Design and Data Mining tools;
  • Develop new tools to streamline Computational Drug Discovery (BIOVIA Pipeline Pilot, Schrodinger Drug Discovery suite, MolSoft ICM Pro) and other tools, and apply them to drug discovery projects, including some open science projects like COVID-19;
  • Participate in new target validation by performing structure-based target assessment, virtual screening to identify new hits, hit expansion, assisting chemists in Hit-to-Lead and Lead Optimization;
  • Assist biologists in streamlining uploading of newly generated biological data and upload data generated by external vendors;
  • Help develop quality, predictive, self-evolving machine learning models for our Tier 1 ADMET set of assays and potency models for our structure-based drug design projects;
  • Present results to internal and external audiences, including at international meetings, and contribute to manuscripts for peer-reviewed international journals;
  • Adhere to all OICR safety guidelines and policies, strongly advocate safety to others.


  • PhD awarded within three to four years in Computational Chemistry, Chemoinformatics or a related field with solid theoretical and practical knowledge of Chemoinformatics, ligand- and structure-based Virtual Screening, Machine Learning and Data Science;
  • Experience in homology modeling, docking and scoring;
  • Proficiency in at least one molecular modeling package, i.e. Schrodinger Drug Discovery suite, MolSoft ICM Pro;
  • Experience in at least one scripting and programming language, such as those included in BIOVIA Pipeline Pilot and/or KNIME;
  • Knowledge of relational databases, understanding organic and/or medicinal chemistry is a plus;
  • Highly motivated and self-dedicated scientist, good team player and excellent interpersonal skills;
  • Written and spoken fluency in English and excellent communication skills;
  • Enthusiasm to work in an interactive, team environment.

The position is for two years, with a possibility of extension to three years. OICR provides competitive fellowships dependent on experience. Please submit your CV/resume, list of publications and a statement of interest.

OICR is an innovative cancer research institute located in the MaRS Centre in the Discovery District in downtown Toronto. OICR is addressing significant challenges in cancer research with multi-disciplinary, multi-institutional teams. New discoveries to prevent, detect and treat cancer will be moved from the bench to practical applications in patients. The OICR team is growing quickly. We are innovative, dedicated professionals who bring expertise to each of our roles. We are looking for individuals interested in being part of a culture of excellence that will result in Ontario being recognized internationally as a leading jurisdiction for cancer research.

Launched in December 2005, OICR is an independent institute funded by the Government of Ontario through the Ministry of Colleges and Universities.

For more information about OICR, please visit the website at www.oicr.on.ca.

CLOSING DATE:       Until Filled

OICR is an inclusive employer dedicated to building a diverse workforce. We encourage applications from all qualified candidates and will accommodate applicants’ needs throughout all stages of the recruitment and selection process. Please advise the Recruiter to ensure your accessibility needs are accommodated throughout this process. Information received relating to accommodation will be addressed confidentially.

The Ontario Institute for Cancer Research thanks all applicants. However, only those under consideration will be contacted.

Resume Format: If you elect to apply, you will need a text or HTML version of your resume so that you can cut and paste it into the application box provided. Before you submit the completed application, you will be asked to attach one or two files to your application. Please attach your resume as a .pdf or .doc file.