Postdoctoral Associate-Biostatistics

Updated: 8 days ago
Location: Durham, NORTH CAROLINA
Deadline: The position may have been removed or expired!
Position ID:Duke -Biostatistics & Bioinformatics -POSTDOC37 [#22852, 210917]
Position Title: 
Position Type:Postdoctoral
Position Location:Durham, North Carolina 27710, United States [map ]
Subject Areas: Statistics / Statistics
Biostatistics / Biostatistics and Data Science
Data Science / Machine Learning
Appl Deadline:none (posted 2022/09/19)
Position Description:    
The department of Biostatistics and Bioinformatics at Duke University School of Medicine is recruiting a postdoctoral associate in the statistical analysis of high-dimensional data and applications in electronic health records supervised by Dr. Anru Zhang. The primary study areas of this position include, but are not limited to, the following: 1. Tensor analysis integrating electronic health records data. 2. Federated learning and computational phenotyping

The candidate will be responsible for developing new methods, benchmarking their performance, and comparing with competing methods, and applying them to large-scale electronic health records data.

Candidates must have or expect to have by the position starting time a Ph.D. degree in Statistics, Biostatistics, Computer Science, Mathematics/Applied Mathematics, or a related quantitative discipline. Candidates with experience in high-dimensional statistics, machine learning, or causal inference are preferred. A strong computational background is required. The initial term for the appointment is two years with the possibility of extensions. The successful candidate will join a team of faculty, staff, postdocs, and graduate students collaborating to create new methods for the analysis of high-dimensional biomedical datasets.

Interested candidates should apply using the following link:
Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.

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