Join the UW Center for Health Innovation & Policy Science and CSDE for the third seminar in our ongoing series on homelessness. On April 20th Graham Pruss will present a talk titled “Vehicle Residency and the Nomadic Turn: How a UW Undergrad Project Drove National Research to Inform Public Policy, Social Services, and Legal Advocacy.”
DEADLINE THIS WEEK: CSDE’s T32 Fellowship Program
CSDE’s Data Science and Demography T32 Fellowship program is accepting applications for a 12-month fellowship for AY 2022-23. This training program is ideal for pre-doctoral candidates who have strong interests in gaining methodological training in data analytics and with research interests in the social determinants or social structural factors linked to population well-being, population health, or demography. The program provides mentoring and support for trainees pursuing scientific careers in relevant academia, government, or private sector organizations. Trainees should be keenly interested in producing scientific knowledge for improving population health and well-being or improving knowledge about population dynamics. Learn more about the program and the application here. You can view a zoom recording of our most recent information session.
Computational Demography Working Group Meeting 4/20!
Join CSDE’s Computational Demography Working Group on Wednesday, 4/20/2022, to hear from Anna Maguire, Senior Research Scientist at Amazon. Anna earned their PhD in Sociology at Vanderbilt 2017. Their research interests are focused on good and bad jobs, work’s impact on health, and the labor movement. You can join the meeting in-person in Raitt 223 or virtually via Zoom.
Summer Network Modeling for Epidemics Workshop: Applications Open for 2022!
Network Modeling for Epidemics (NME) is a 5-day short course at the University of Washington that provides training in stochastic network models for infectious disease transmission dynamics.
This is a ”hands-on” course, using the EpiModel software package in R (www.epimodel.org). EpiModel provides a unified framework for statistically based modeling of dynamic networks from empirical data, and simulation of epidemic dynamics on these networks. This course will touch on the deterministic and individual-based models, but its primary focus is on the theory, methods and application of network models. The course uses a mix of lectures, tutorials, and labs with students working in small groups.