CAHFS Internships

The Center for Animal Health and Food Safety (CAHFS) hosts veterinary and animal health scholars at the University of Minnesota as part of the CAHFS Internship program. Interns join the University to develop their projects in collaboration with the CAHFS team, and are mentored by leading faculty and researcher experts. 

Potential areas of focus

  • Risk analysis applied to animal health and food safety
  • Quantitative epidemiology and disease modeling
  • Spatial analysis
  • Evaluation of diagnostic techniques
  • Training on veterinary laboratory diagnostics (In partnership with the Minnesota Veterinary Diagnostic Laboratory)


Gray Background with padding
icon of the outline of China

Xie Yihong – 
Guangxi Centers for Disease Control, China

In summer 2018, Xie Yihong traveled from the Guangxi region in China to the Twin Cities to study food safety with Dr. Andres Perez and the research team in CAHFS. As the current deputy head and associate chief physician in the Division of Food Safety Monitoring and Risk Assessment of the Guangxi Centers for Disease Control, Dr. Xie’s interests focused on risk assessment as applied to fish health. Read more about Dr. Xie’s experience.

icon of the outline of Thailand

Orapun Arjkumpa – Department of Livestock Development, Thailand

Orapun Arjukumpa joined the CAHFS research team in the summer of 2019 from Chiang Mai University, Thailand to conduct data analysis on foot and mouth disease in northern Thailand. Dr. Arjukumpa worked with Catalina Picasso, post-doctoral researcher in CAHFS, to conduct disease modeling and continue work on her PhD in the Faculty of Veterinary Medicine. 


icon of the outline of Uruguay

Nicole Rosenstock – Universidad de la República Oriental, Uruguay

Nicole Rosenstock's research focused on network analysis applied to the epidemiology of infectious diseases with an impact on public health. Dr. Rosenstock worked with U of M experts including Kim VanderWaal in the Department of Veterinary Population Medicine to learn new skills in working with big data, statistical analysis, and new software such as RStudio.