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Overview
Seasonal Influenza in the United States causes an annual average of 25m infections, 400k hospitalizations, and 32k deaths, which result in 11B in total medical costs. To improve public health decision making and situational awareness, the Centers for Disease Control and Prevention asks for computational forecasts of the number of incident hospitalizations due to influenza for every state in the US. This CDC system is called the FluSight Project.
The Computational Uncertainty Lab has modeled influenza for several years to improve the health and well-being of others by contributing to FluSight, giving state-level public health officials forward-looking information about influenza so that they can best prepare the public.
As an Influenza Forecaster in the Computational Uncertainty Lab, you will support public health preparedness by contributing weekly influenza forecasts to the FluSight project.
Eligibility
This opportunity is for MS Data Science Students at Lehigh University who are participating in the “Research Match”. This position can consider those outside the Research Match who are active students at Lehigh University.
Length of Project
Starts in Fall 2026 and Ends Spring 2027 (including Winter).
Research credit
This project can be considered as an independent study, thesis (with approval of the Data Science Program), or non-credit research.
Payment
At this time this position is an experience-based, unpaid research opportunity. This may change over time and applicants can request a discussion on this topic.
Skills
MS students should be well-versed in the following skills:
- Python programming, debugging, code revision/update/building
- The use of the shell, terminal and scripting (an understanding of Makefile is a plus)
- Git and GitHub including Add/Push/Commit/Pull Requests
- Probability and Statistics, with a preference toward:
- Linear Algebra and Multivariate Calculus to support Prob/Stat
- Bayesian statistics
- Basic Ordinary Differential Equations and Systems of Equations
Responsibilities
Under supervision of a Postdoctoral Research Fellow and PI (McAndrew), the MS Data Science student will be expected to train a suite of computational models that generate 1–4 week ahead forecasts and submit an ensemble forecast to the CDC FluSight project. Training and submissions occur on every Wednesday for approximately 34 weeks, starting in Fall and ending Spring. The MS Data Science student is expected to join weekly meetings with PI and Postdoc to discuss model results that are then prepared for submission. During the influenza season, the student is expected to join calls with Council of State and Territorial Epidemiologists that discuss infectious disease modeling.
Contact
Please reach out to Professor McAndrew (PI) at mcandrew@lehigh.edu about the position.