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Post Doctoral Fellow, Statistical/AI Methods for Genomic/Microbiome Analysis
Company Information
The Wu Group’s research focuses on the development and deployment of new statistical, computational, and (more recently) AI-based methods within the broader context of clinical and population-based studies. Methods developed by the group represent key components of many analytic pipelines. Currently, the group is heavily invested in developing and applying cutting-edge approaches for microbiome and metagenomic studies. The group is part of the Biostatistics Program of the Fred Hutchinson Cancer Center.
The fellow will be primarily involved in developing statistical or AI (Large language model) methodology within the context of genomic, spatial proteomic imaging, and microbiome studies. The specific areas of methodological research can be flexible, and proposed projects will be tailored to the fellow’s interests and experience. Many challenges exist in analyzing these new types of data, providing exciting opportunities for the development of novel statistical methods. With the data being directly collected from forefront research projects, this work has the potential to be truly high-impact.
The fellow will be supervised by Dr. Michael Wu (https://research.fredhutch.org/wu/) and will join an active research group. The fellow will also have the opportunity to interact with other statistical researchers and develop a national network of mentors and collaborators, providing a supportive and enriching environment for the fellow’s growth.
(1) Ph.D. or equivalent in Statistics, Biostatistics, or a similar quantitative field.
(2) Excellent written and oral communication skills