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.
Preferred QualificationsLearning 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.
Skills Required
- Experience developing and evaluating machine learning models, specifically Graph Neural Networks
- Proficiency in R and/or Python for data analysis and modeling
- Experience with time-series forecasting methods and model validation
- Experience analyzing public health surveillance data (e.g., ED visits, hospitalizations, lab testing, immunizations, wastewater)
- Ability to build reproducible analytical workflows and create visualizations
- Experience documenting methodologies and supporting knowledge transfer
- Familiarity with model deployment practices
What We Do
Boston Public Health Commission is Boston’s health department, working in partnership with communities to protect and promote the health and well-being of all residents, especially those impacted by racism and systemic inequities. It offers over 40 programs and services including family and child health, recovery services, and emergency shelter.
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