Data-Driven HPAI Modeling for Cattle Health

Oak Ridge Associated Universities; Fort Collins (CO); On-site; USD 64,000 - 90,000; Full time

Job summary

Oak Ridge Associated Universities (ORAU) administers the ORISE program hosted by USDA APHIS in Fort Collins, Colorado. This research opportunity focuses on developing data-driven models to characterize cattle herds with prolonged HPAI detection and improving understanding of disease dynamics and response strategies.

Participants collaborate with scientists and decision-makers, gain experience in risk-based surveillance approaches, and learn to evaluate diagnostic-test performance.

Qualifications

• The qualified candidate should have received or be currently pursuing a master's or doctoral degree in one of the relevant fields (e.g. Statistics, Biostatistics, Epidemiology, Ecology, Operations Research, Biology, Veterinary Medicine).

Responsibilities

• Collaborate with scientists and decision-makers to collect and integrate field data for development of HPAI risk models and analytical tools.
• Develop skills in evaluating diagnostic-test performance and interpreting implications for disease detection and surveillance design.
• Gain experience analyzing risk-based surveillance approaches and quarantine-release strategies to support monitoring, response, and control efforts.

Skills

Biological modeling

Bayesian statistics

Study design

R/GitHub + Bayesian MCMC

Education

Master's or PhD in Statistics/Biostatistics/Epidemiology/Ecology/OR/ Biology/ Veterinary Medicine

Tools

R

GitHub

JAGS

Stan

NIMBLE

Job description

Oak Ridge Associated Universities (ORAU) administers the ORISE program hosted by USDA APHIS in Fort Collins, Colorado. This research opportunity focuses on developing data-driven models to characterize cattle herds with prolonged HPAI detection and improving understanding of disease dynamics and response strategies.

Participants collaborate with scientists and decision-makers, gain experience in risk-based surveillance approaches, and learn to evaluate diagnostic-test performance.