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Image Analyst

dfjdnwyykvmxdk0vhx9jct2ohu8qb009027a14rpuk03y2aq7vr2un93qru1r2ro · 30+ days ago

Mississauga, ON, CA

Negotiable

Full-time

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We are seeking a highly motivated analyst to process the in-house images and analyze the data for ongoing projects. The successful candidate would process and analyze the microscopy images for on-going scientific projects, as well as contribute to the code base of soft wares being developed in-house. The analyst will need to work closely with both experimentalists and statisticians to ensure that data and results are communicated smoothly.

Principal Duties and Responsibilities
• Under the supervision of project manager, investigate and apply the best-in-class algorithms to process raw microscopy image, extract tabular information from images, assess the quality of the data and carry out statistical analysis
• Work closely with cross-functional teams to understand analytical needs, independently and collaboratively formulate analysis plan and implement corresponding analytical workflows, and actively participate in discussions with stakeholders for feedback
• Code in Python for image processing and analysis tasks
• Effectively present analysis results in a clear and concise manner to key stakeholders

Must-Have Qualifications
• PhD in Bioinformatics, Computer Science, Machine Learning, Statistics or Computational Biology. Alternatively, you have a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area.
• 3+ years experience (including any graduate school) developing or applying biomedical image processing tools and statistical analysis softwares of microscopy image data.
• Comfortable with the statistical principles behind current best practices in high-throughput molecular data analysis.
• Experience in the Python biomedical image analysis ecosystem, including scipy, scikit-image, imageio, xarray, scikit-learn.
• Demonstrated ability to effectively communicate about complex bioinformatics problems to peers, users, and stakeholders.
• Motivated to learn new biology, technology and analytical methods

Nice-to-Have Expertise
• Familiarity with deep learning approaches for cell segmentation, feature extraction, and phenotypic analysis
• Familiarity with high-dimensional multiplexed imaging data and associated data/image models
• Familiarity with domain-specific image processing tools, such as cellpose, cellprofiler and stardist
• Familiarity with workflow development tools, such as Snakemake or Redun
• Analysis of large chemical/genetic screening datasets
• Single-cell genomics and trajectory analysis

•

Last updated on Oct 17, 2023

About the company

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dfjdnwyykvmxdk0vhx9jct2ohu8qb009027a14rpuk03y2aq7vr2un93qru1r2ro

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