Research Associate in Mathematical Statistics GS-1529-11
Bayesian Hierarchical Spatial Statistical Modeling and Machine Learning
USDA-ARS (located at University of Missouri) and collaborators are involved in federally funded, crosscutting research in Bayesian hierarchical spatial modeling and machine learning with applications to soil health and carbon cycling. As a result, the USDA-ARS plans to appoint a postdoctoral fellow to be a key contributor to this research. The appointment is for one-year with expectation of renewal for a second year. The position will remain open until filled and can start anytime.
The research associate will develop and implement novel and innovative statistical methodologies intended to improve the analysis of high-dimensional spatial functional data with agronomic applications. This position will focus on development and integration of statistical and machine learning methodologies to handle complex data distributions at the continental scale. The methodology will be applied to large datasets from USDA and collaborators. The research is expected to strengthen current soil health assessment tools, improve the understanding of the spatial distribution of soil properties at the continental scale, and quantify anthropogenic and climate impacts on soil carbon. This improved modelling approaches will contribute to development of more sustainable agricultural production systems and best management strategies for carbon sequestration.
Applicants must have received, or expect to complete, a doctorate in statistics or related discipline within the last 5 years. Women and members of under-represented groups are particularly encouraged to apply. Selection criteria will include demonstrated research ability in statistics or a relevant scientific discipline, interest in hierarchical spatial modeling and machine learning, Bayesian methodology and computation, experience with dimension reduction and analysis of high-dimensional datasets, commitment to collaborative research, and excellent verbal and written communication skills.
The research associate will participate in research leading to publications in top statistical and domain science journals and present research results at conferences.
To apply E-mail (PDF files if possible) the following items to kristen.veum@usda.gov (1) a letter of interest, containing full contact information, year graduated and citizenship/immigration status, concisely responding to the research emphases and criteria above; (2) a CV listing educational background, research experience and publications; and (3) abstracts of the dissertation and any publications. The cover letter or CV should include names and contact information for three references (no letters please). Please indicate “Mathematical Statistics Postdoc” in the subject field of the message.
Screening of applications will begin immediately and the application pool will remain open until the position is filled.