The University of Chicago's Section of Rheumatology is looking to improve and maintain algorithms for accurate detection, segmentation, and classification of cells and structures in biomedical microscopy images, align high dimensional (HD) images of human tissue to conventionally stained sections, and train a machine learning network to detect textures in H&E which correspond to specific inflammation and damage states revealed by HD imaging.
Requirements
- Proficiency in Python and BASH; familiarity with SLURM and PyTorch.
- Proficiency in machine learning specifically CNNs.
- Familiarity with processing and managing image data.
- Skills in basic bioinformatics.
Responsibilities
- Optimize and maintain algorithms for accurate quantification of biomedical microscopy images.
- Train a machine learning (CNN) network to identify inflammation and damage patterns on H&E sections.
- Validate performance of algorithms on novel datasets.
- Properly version and document all updates and additions to code and pipelines.
- Work with a team to drive innovation when analyzing new data.
- Assists in analyzing data for the purpose of extracting applicable information.
- Performs research projects that provide analysis for a number of programs and initiatives.
Other
- 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 or Data Science.
- Previous data science experience.
- Resume/CV (required)
