Job Description

Union: Non-Union
Number of Vacancies: 1
New or Replacement Position: New
Site: Princess Margaret Cancer Centre
Department: Research
Reports to: Principal Investigator
Salary Range: $31.03 - $46.84 hourly
Hours: 37.5 hours a week
Shifts: Monday - Friday
Status: Temporary Full-Time (1 year contract)
Closing Date: September 16, 2026 (repost)

Position Summary

Our lab is a multidisciplinary research program based at the Princess Margaret Cancer Centre, University Health Network, and closely integrated with the Structural Genomics Consortium. We operate at the intersection of clinical oncology, experimental biology, and functional genomics, with a focus on understanding chromatin architecture, epigenetic regulation, and tumor heterogeneity in cancer.

The lab uses 3D genome mapping, chromatin profiling, next-generation sequencing, patient-derived models, and multi-omic approaches to identify regulatory mechanisms that may inform precision oncology strategies, biomarker discovery, and epigenome-informed therapeutic approaches.

We are seeking a highly motivated Research Technician with strong wet-lab experience to support and execute experimental projects in cancer epigenomics and 3D genome biology. The successful candidate will contribute to projects involving chromatin conformation assays, functional epigenomics, next-generation sequencing library preparation, and patient-derived model systems.

This position is ideal for a candidate with hands-on experience in molecular biology, genomics, epigenomics, and cancer biology who is interested in working in a collaborative, translational research environment.

Duties

• Perform and optimize molecular biology and functional genomics experiments related to cancer epigenomics.
• Carry out chromatin and sequencing-based assays, including Hi-C, HiChIP, ATAC-seq, CUT&RUN, CUT&Tag, and related methods, as applicable.
• Prepare next-generation sequencing libraries across multiple assay types.
• Work with patient-derived cancer models, including organoids or related culture systems.
• Support sample processing, quality control, library preparation, and coordination of sequencing submissions.
• Maintain accurate experimental records, protocols, sample inventories, and laboratory documentation.
• Assist with troubleshooting and optimization of complex wet-lab protocols.
• Coordinate with computational scientists and other team members to support data generation, interpretation, and project progress.
• Contribute to the generation of figures, summaries, and experimental documentation for manuscripts, grants, presentations, and reports.
• Assist with ordering, reagent preparation, equipment maintenance, and general laboratory organization.
• Support training of junior lab members or students in established protocols, as appropriate.
• Contribute to a collaborative, rigorous, and well-organized lab environment.

Qualifications

• At minimum, Bachelor's degree in Molecular Biology, Cancer Biology, Genetics, Genomics, Biochemistry, Cell Biology, or a related field required
  • Master's degree an asset
• Minimum of 3 years of relevant wet-lab research experience required
• Strong hands-on experience with molecular biology and genomics techniques.
• Experience with next-generation sequencing library preparation.
• Experience with chromatin-based or epigenomics assays, such as ATAC-seq, CUT&RUN, CUT&Tag, Hi-C, HiChIP, Capture-C, or related methods.
• Experience with patient-derived organoid culture or other cancer model systems.
• Ability to follow, optimize, and troubleshoot complex experimental protocols.
• Strong organizational skills and careful attention to detail.
• Ability to maintain clear and accurate experimental records.
• Excellent communication skills and fluency in English, written and spoken.
• Ability to work effectively in a collaborative, multidisciplinary research environment.
• Ability to manage multiple experimental tasks and timelines.
• Direct experience with 3D genome assays, such as Hi-C, HiChIP, Capture-C, Micro-C, or related methods an asset
• Experience with single-cell or spatial genomics workflows an asset
• Experience with low-input or challenging clinical/research samples an asset
• Basic familiarity with genomic data analysis concepts and tools, including R, Python, command-line environments, or sequencing QC metrics an asset
• Experience working in a translational cancer research environment an asset
• Prior experience contributing to manuscripts, reports, or grant-related experimental summaries an asset

Additional Information