Postdoctoral Researcher
$54,902–$93,333 year
On-site · Toronto, Ontario, Canada
Job Summary
A computational postdoctoral researcher position is available in the laboratory of Dr. Gregory Schwartz to study cellular diversity in response to anti-cancer therapies. The Schwartz Lab develops novel multi-omic and single-cell computational methods to improve cancer diagnosis and treatment through precision medicine. Responsibilities include working with data from cutting-edge technologies (single-cell transcriptomics, single-cell epigenomics, spatial transcriptomics, spatial multiomics), developing novel computational methods to identify cellular populations using multiomic integration, tracking cancer-cell evolution across treatments with deep-learning architectures, identifying biomarkers associated with different anti-cancer treatments, determining tumor microenvironmental factors linked to disease progression and treatment resistance, disseminating research through conferences and high-impact publications, developing reproducible pipelines for high-throughput data analysis, and contributing to grant applications. A PhD is required in a relevant field, and a strong publication record and programming experience are expected. The role offers a temporary full-time appointment for an initial one-year term with potential renewal; location is at Princess Margaret Cancer Centre, Toronto, Canada.
Required Qualifications
- PhD awarded within the last 5 years in Computer Science, Mathematics, Bioinformatics, Computational Biology, or a related field
- Proven track record of published method development
- Strong background in Linux and Python
- Strong background in statistics, machine learning, and/or deep learning
- Excellent writing and verbal communication skills
- Experience with version control (Git/GitHub)
- Experience with next-generation sequencing data formats such as FASTQ, BAM, Matrix Market, and HDF5 is a plus
- Experience with Haskell, R, and LaTeX is a plus
- Willingness to work in a team environment as well as independently
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