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One postdoctoral associate position on infectious disease geospatial modeling is available in the Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University. Applicants with a background in spatial statistics, spatial network models, geospatial analysis or spatial epidemiology are highly encouraged to apply. Our group focus in the epidemiology of transboundary animal diseases integrating approaches such as traditional spatiotemporal statistics for practical mapping the spread of infectious diseases, and forecasting disease emergence in animal and human populations. Main role: We are searching for a motivated postdoctoral researcher to co-lead the development of new computational tool for analyzing the spread of swine diseases. This position will be center in the development of mechanistic models which explicit consider transmission dynamics in space and time. The focus here is in the development and dissemination of a forecast treatment regimen for precision and optimal resource allocation to help the swine industry to efficiently preempt and manage outbreaks. Ultimately, this framework will help the industry to efficiently preempt and manage endemic and emerging diseases. The postdoctoral researcher will fit models to a unique data that has been fully collected and curated. The available dataset include: full animal movement data at farm level, weekly disease occurrence with genetic sequences, complete biosecurity and disease intervention for a span of two years and more. In summary, this work will unravel transmission, estimate epidemic parameters, identify spread determinants and assess the impact of interventions. In addition, a number of potential research projects are available and so the research focus may be tailored to the interests and skills of the individual. There will also be opportunities to seek grant funding to develop related, independent research. Access to high-powered computing is available through the Machado's lab.
Environment: The Machado Lab develop and deploy epidemiological methods which fully integrate disease evolution, animal movement, spatial processes to estimate disease transmission and spread. Ultimately we work in the development of new computational surveillance tools for both tracking spread and prescribing treatment regimens. New members, will work in a group with strong background in epidemiology, disease spread modeling, evolutionary epidemiology, social networks and mathematical modeling. New member will benefit from the national and international collaboration networks that our lab have developed.
Duties & Responsibilities: Collect and organize data for research activities. Collaborate with the PI in the generation and testing of research hypotheses and data analysis, writing of papers, grants, and reports, and preparation of presentations and lectures. Participate in laboratory meetings, seminars, graduate and undergraduate lectures, and conferences as needed. As part of the position, the candidate will publish and present their work at conferences. Position terms: The initial appointment will be from 12 to 18 months, but three years of federal funding have already been secured.
Ph.D. or equivalent doctorate (e.g., M.D., D.V.M., Sc.D.) in appropriate field awarded no more than five (5) years from initial date of postdoctoral appointment.
It is critical that the selected candidate have moderate to extensive experience in R or other open-source related statistical software. - Previous work related with spatial analysis, network analysis. – Practical experience with building spatially explicit models, particularly those that are also process-based and mechanistic model development. – Evidence of original publications in the peer-reviewed literature. – Good communication and experience in developing grant proposals and take the lead in projects. – Ability to work independently and in collaboration.
The ideal candidate has a Ph.D. degree in a relevant quantitative discipline (ecology, epidemiology, applied mathematics, physics, statistics, or other quantitative field). –Prefer applicants with previous experience with multi-scale models and ensemble methods.
Required license or certification:
Position Number: 00108087
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