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Postdoctoral Fellow
Department of Mathematics and Statistics in Washington,
 
 
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Date Posted 02/05/2021
Category
Admin-Other Administrative Positions
Employment Type
Application Deadline Open until filled
 
 
 
 
 
The Department of Mathematics and Statistics at Georgetown University (https://mathstat.georgetown.edu/ ) is seeking a postdoctoral fellow to work on a wide range of statistical methods and applications. The postdoc will have the flexibility to choose research projects and mentor(s) among the statistics faculty members in the department. Possible research topics include: establishing theoretical links between hierarchical Bayesian models and machine learning methods, developing/extending methods for variable selection and the identification of latent structures in high-dimensional data, integrating heterogeneous datasets, modeling complex count data, spatio-temporal data and multivariate longitudinal data. Motivating applications include: ecology studies of climate-driven phenomena, epidemiological studies and biomedical studies involving -omic data (epigenomic, genomic, transcriptomic, metabolomic, metagenomic).

Candidates should have a doctoral degree in statistics, biostatistics, data science or a related field. Strong computational skills and expertise in Bayesian modeling are desired. This is a two-year position with a start date of July 1, 2021. Applicants should submit a CV, a cover letter and contact information for two academic references. The cover letter should include a brief description of the applicant’s current research. Application reviews will start immediately. For any questions, contact Mr. Robert Pike (rfp32@georgetown.edu).

Georgetown University is an Equal Employment Opportunity Affirmative Action employer. The University seeks to provide equal opportunity in employment for all persons, and prohibits discrimination in all aspects of employment because of age, citizenship, color, disability, marital status, national origin, race, religion, personal appearance, family responsibilities, matriculation, political affiliation, sex, sexual orientation, gender identity and expression, and genetic information or veteran status or any other basis prohibited by law.

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