Job Title

OverviewWe're looking for a bioinformatics scientist to support analysis of image-based assays for a confidential large pharmaceutical client, with a strong emphasis on optical pooled CRISPR screening and spatial transcriptomics workflows in a discovery research environment. A solid foundation in working with microscopy imaging data and image-based analysis workflows is essential and is the core requirement for the role.This role sits at the intersection of fluorescence microscopy and computational biology. You'll work closely with bench scientists and computational team members to process and analyze imaging data, improve existing workflows, and generate high-quality outputs from complex biological assays, including Optical Pooled CRISPR, and may include spatial transcriptomics and proteomics data from platforms such as CosMx, Xenium, Atera, Element Bioscience, Singular Genomics, COMET, and Cellscape.This is a contractor role focused on execution, ideal for someone who understands microscopy data deeply and can apply computational methods to analyze and improve results. You are proactive, detail-oriented, and comfortable working independently in a remote, part-time capacity while staying tightly integrated with a collaborative research team.What you'll doAnalyze imaging data from optical pooled CRISPR screening and related biological assays, including cell paintingWork with and modify existing analysis pipelines covering segmentation, feature extraction, and quality controlApply image analysis techniques, both classical and ML/AI-based, to identify and quantify cellular phenotypes in an AWS cloud environmentProcess and analyze spatial transcriptomics and proteomics data from platforms including CosMx, Xenium, Atera, Element Bioscience, Singular Genomics, COMET and CellscapeAssess image quality, diagnose acquisition artifacts, and recommend improvements at both the instrument and bench levelCollaborate with bench scientists to interpret results and troubleshoot issuesBuild automated reporting tools or R Shiny applications to communicate results to scientific stakeholdersMaintain rigorous, reproducible code using GitHub version control with clear pipeline documentationRequired skillsProficiency in Python (preferred) and R, with demonstrated experience writing clean, documented codeExperience in computational biology and bioinformatics applied to real biological datasets in mammalian cellsExperience working with microscopy or image-based biological dataExperience modifying or working within existing analysis pipelinesFamiliarity with workflow tools: Nextflow preferred, Snakemake or similar acceptableAbility to critically evaluate cell segmentation performance using qualitative and quantitative metricsStrong communication skills with the ability to translate complex computational outputs clearly for biological audiencesPreferred experienceOptical pooled CRISPR screening or high-throughput imaging assays (e.g., cell painting)Image analysis tools such as CellProfiler, CellPose, FIJI/ImageJ, QuPath, Halo, SimA, or IlastikExperience troubleshooting segmentation and feature extraction workflowsSpatial transcriptomics and proteomics platforms including CosMx, Xenium, Atera, Element Bioscience, Singular Genomics, COMET and CellscapeSingle-cell or bulk RNA-seq preprocessing and analysisCloud environments (AWS) and containerization (Docker)Wet lab or bench research background that enables natural collaboration with experimental scientistsEngagement DetailsContractor role, approximately 20 hours per week. Remote with a flexible schedule. Opportunity for extension based on performance. Applications are reviewed on a rolling basis and the role is open immediately.Compensation$35 to $65 CAD per hour, depending on depth of experience with microscopy workflows, optical pooled screening, and ability to operate independently.