Digital Pathology AI Developer

Qualifications

• We're looking for individuals with a current enrollment in or recent graduation from a Computer Science, Biomedical Engineering, Medical Data Science, or related program
• Strong Python programming skills and experience with deep learning frameworks like PyTorch or TensorFlow are required
• Familiarity with foundation models and their applications in AI and data science is also necessary

Responsibilities

• As an AI & Data Science Intern, you'll be responsible for developing a functional prototype using foundation model embeddings to extract biologically relevant features from Whole Slide Images (WSIs)
• You'll design and implement scalable data processing pipelines, including feature extraction, quantification, and visualization
• Additionally, you'll analyze extracted features to improve searchability, classification, and dataset insights in pathology AI applications
• Working with cross-functional teams to integrate models and datasets into existing workflows
• Documenting findings, methodologies, and results to contribute to team knowledge sharing

Full Description

Your Role

As an AI & Data Science Intern, you'll be responsible for developing a functional prototype using foundation model embeddings to extract biologically relevant features from Whole Slide Images (WSIs). You'll design and implement scalable data processing pipelines, including feature extraction, quantification, and visualization. Additionally, you'll analyze extracted features to improve searchability, classification, and dataset insights in pathology AI applications.

Key Responsibilities Include:

• Working with cross-functional teams to integrate models and datasets into existing workflows.

• Documenting findings, methodologies, and results to contribute to team knowledge sharing.

Our Requirements

We're looking for individuals with a current enrollment in or recent graduation from a Computer Science, Biomedical Engineering, Medical Data Science, or related program. Strong Python programming skills and experience with deep learning frameworks like PyTorch or TensorFlow are required. Familiarity with foundation models and their applications in AI and data science is also necessary.