The University of Chicago's Section of Hematology/Oncology is looking to solve the problem of accurate detection, segmentation, and classification of cells and structures in biomedical image data, as well as analyzing spatial transcriptomic data to evaluate spatial patterns of genes in tissues, specifically in the tumor microenvironment of breast and bladder cancers.
Requirements
- Proficient in Python with a familiarity of specific libraries/APIs including sci-kit learn, pandas, skimage, and PyTorch.
- Proficiency in Python, BASH, SLURM and PyTorch; familiarity with R.
- Experience processing and managing both image and tabular data.
- Analytical skills.
- Problem-solving skills.
- Attention to detail.
- Organizational skills.
Responsibilities
- Optimize and maintain algorithms in biomedical image analysis pipelines.
- Validate algorithm performance on novel datasets.
- Analyze spatial transcriptomic data.
- Perform statistical analyses on data extracted form bio-images and other spatial data.
- Documentation and versioning of code and results.
- Assists in analyzing data for the purpose of extracting applicable information.
- May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.
Other
- Strong interpersonal and communication skills.
- Ability to work independently and as a team.
- Minimum requirements include a college or university degree in related field.
- Minimum requirements include knowledge and skills developed through < 2 years of work experience in a related job discipline.
- Advanced degree in Computer Science, Bioinformatics, or Data Science (preferred).
