Description:
We are looking for an U-M Masters or PhD student with strong statistical and computational skills with an interest in aiding in the design, implementation, and analysis of a large-scale individual-based simulation model of infectious disease transmission. This position is part of a multidisciplinary project funded by MICDE’s Catalyst program and led by Dr. Jon Zelner of the Dept. of Epidemiology, UM School of Public Health and Dr. Seth Guikema of the Dept. of Industrial and Operations of Engineering at the UM College of Engineering.
This project will involve integration of statistical and machine learning tools into an individual-based simulation model, allowing opportunities to develop experience in both of these domains. Statistical methods employed include non-parametric smoothing, Gaussian process regression, conditional autoregressive spatial models, and hierarchical Bayesian regression. The final model will likely be implemented in R, Python, C/++, Julia, or some combination thereof.
We anticipate a commitment of up to 10 hours per week during the academic year, with the possibility of a full-time position during the summer of 2020.
Compensation: $18 per hour
How to apply: Please email a CV and short description of skills and interest in this project to Jon Zelner at [email protected].
