Our group focus in the epidemiology of transboundary diseases integrating biogeographic approaches and traditional spatio-temporal statistics for practical mapping the spread of infectious diseases, and forecasting disease emergence in animal and human populations. In addition, we develop the next generation machine learning tool set that will incorporate temporal effect for disease intelligence predictions. We combine data and epidemiological analysis with spatial and non-spatial epidemiology to study disease distribution and forecasting, ultimately to design control measures to protect business continuity in an FAD outbreak and reduce the public health burden associated with infectious diseases. our research is supported by USDA.

Duties: The candidate's research projects will focus on the animal and human infectious disease, where spatial and temporal dimensions of infectious disease outcomes within the environment will be applied to health surveillance. The development epidemiological tools to investigate the occurrence and spread of animal infectious diseases, especially transboundary disease, providing science-based support for decision making with regard to prevention and control are expected to be used and, or will work in the development or translation of innovative methods to be applied in the epidemiology of transboundary diseases. The candidate will work in a multidisciplinary team with veterinary epidemiologists, public health researchers.

Necessary Education, Experience Skills, Training and Education: The postdoctoral associate must have Ph.D. degree in a relevant quantitative discipline (ecology, epidemiology, engineering, applied mathematics, physics, statistics and related fields). Proficiency in programming with R or similar open-source platform. Strong oral and writing skills are necessary. Desired qualifications include good communication and experience in developing proposals. Previous experience with spatial and spatio-temporal statistics or biogeographic approaches including niche modeling or machine learning algorithms. Experience developing and implementing spatial and spatio-temporal model is desirable. Applicants must have the ability to work independently and in collaboration.
The initial appointment will be for one year, with renewal for two or more years subject to satisfactory progress and mutual agreement. The salary will be commensurate with the qualifications and experience of the individuals. Review of applications will begin immediately and will continue until suitable candidates are identified.
How to apply

Interested applicants should submit a 1) a letter of intent highlights your research interests, interest in and interest in infectious diseases; 2) curriculum vitae; 3) sample of scientific writing (e.g., a manuscript in preparation, an undergraduate thesis), and the names and contact information for three references to gmachad@ncsu.edu