Bayesian Modeling for Environmental Health at Columbia University 2025

Master Bayesian modeling in Environmental Health through interactive seminars and hands-on sessions in this two-day workshop. Gain practical insights into concepts, techniques, and data analysis methods.A two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications in Environmental Health.

Table of Content

• Summary
• Benefits
• Requirments
• Application Deadline
• How To Apply

Summary

• Application DeadlineAugust 15, 2025
• Study LevelUndergraduate
• SponsorColumbia University

Benefits

A two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications in Environmental Health.

Requirements

• Basic familiarity with R and R studio (how to download R/R studio, and how to install a package) is recommended to get the most out of the workshop.
• Familiarity with spatial and temporal data structures, as well as exponential family distribution types (normal, Poisson etc.) would also be useful, though not essential.
• Each participant is required to bring a personal laptop as all lab sessions will be done on your personal laptop. Each participant will be using RStudio Cloud to carry out tasks while attending the Workshop. Instructions for the basics of RStudio Cloud(link is external and opens in a new window).

Application Deadline

How To Apply

• Learn the principles of Bayesian modeling in Environmental Health through interactive seminar lectures, gaining a solid understanding of the underlying concepts.
• Engage in hands-on computer sessions to apply theoretical knowledge practically. Explore existing data examples and initiate discussions on launching investigations based on participants' research questions.
• Acquire practical know-how on dealing with different data structures and explore various software options available for Bayesian modeling, empowering learners to navigate diverse analytical tools.
• Benefit from the extensive experience of the workshop's scientist-led team. Receive a comprehensive overview of Bayesian inference principles, different analysis types, and insights into current and future research in Environmental Health.

For more details visit Columbia University Scholarship Webpage