Student Assistant - Pathology
Core
Assist in the development, testing, and validation of artificial intelligence and deep learning models applied to digital pathology and precision oncology by analyzing whole-slide histopathology images and managing data pipelines.
Role type
Student Assistant (AI/ML Research)
Builds
AI models for cellular segmentation, glandular architecture analysis, and disease recurrence prediction
Domain
Digital Pathology / Precision Oncology / Computer Vision
Deliverable
production ML models
Required skills
Python programming, machine learning, deep learning frameworks (PyTorch, TensorFlow), data preprocessing, image tiling, quality control pipelines, literature review, code documentation, GitHub
Preferred skills
digital pathology libraries (OpenSlide, HistomicsTK), high-performance computing (HPC), GPU acceleration, oncology/biology concepts
Technologies
PyTorch, TensorFlow, OpenSlide, HistomicsTK, GitHub
Responsibilities
Pull, organize, and preprocess large datasets of whole-slide images; implement image tiling and normalization pipelines; support implementation and training of deep learning architectures; conduct targeted literature reviews on computational pathology; document code and maintain shared repositories; participate in weekly lab meetings and present project updates
Seniority
Undergraduate or early graduate student