Summer Research Assistant: AI Image Analysis in Pathology

The Chronicle Of Higher Education, Inc.; Richmond (VA); On-site; USD 17,047 - 24,280; Part time

Benefits offered by this job

Wide array of employee benefits

Job summary

The Chronicle Of Higher Education, Inc. seeks an undergraduate research assistant for the School Of Medicine's Cellular and Genetic Medicine Department at VCU. The candidate will engage in computational pathology research, gaining hands-on experience and contributing to peer-reviewed studies.

This role includes developing machine learning models and working closely with faculty to analyze biomedical imaging data. A commitment of up to 25 hours per week, with flexible scheduling around classes, is essential.

Qualifications

• Experience in programming and machine learning or computer vision projects.
• Commitment to weekly hours throughout the semester.
• Ability to work professionally with diverse groups.

Responsibilities

• Develop, train, and evaluate models for biomedical image analysis.
• Implement digital pathology pipelines for WSI processing.
• Organize and annotate image datasets with expert coordination.
• Write clean, well-documented Python code.
• Maintain reproducible experiments using version control.
• Participate in lab meetings and present findings.

Skills

Programming (Python preferred)

Data structures

Machine learning or computer vision

Deep learning frameworks (PyTorch or TensorFlow)

Data curation and annotation

Education

Currently enrolled or completed Bachelor's in Computer Science or related

Tools

Git

Jupyter

PyTorch

TensorFlow

OpenCV

OpenSlide

QuPath

Job description

The Chronicle Of Higher Education, Inc. seeks an undergraduate research assistant for the School Of Medicine's Cellular and Genetic Medicine Department at VCU. The candidate will engage in computational pathology research, gaining hands-on experience and contributing to peer-reviewed studies.

This role includes developing machine learning models and working closely with faculty to analyze biomedical imaging data. A commitment of up to 25 hours per week, with flexible scheduling around classes, is essential.