Graph Neural Network Influenza Modeling Intern

The Graph Neural Network (GNN) Influenza Modeling Intern will support the development and evaluation of machine learning models to improve seasonal influenza forecasting. The intern will analyze historical and current influenza surveillance data, develop and validate forecasting models using Graph Neural Networks, and assess how integrating multiple public health data sources—including emergency department visits, hospitalizations, laboratory testing, immunizations, and wastewater surveillance—affects predictive accuracy. The intern will also build reproducible R and/or Python workflows, support model visualization and deployment, and document processes to ensure long-term sustainability of the forecasting model.

Learning Objectives

• Gain experience with influenza surveillance systems and public health data sources.
• Learn and compare traditional forecasting methods with machine learning and Graph Neural Network approaches.
• Develop and evaluate forecasting models using R and/or Python.
• Build reproducible analytical workflows and visualizations for public health applications.
• Document methodologies and support knowledge transfer to BPHC staff.