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Post-doctoral Associate in Statistical Genetics/Omics and Deep Learning

Company Information

A post-doc position is available now (until filled) in the Division of Biostatistics and Health Data Science at the University of Minnesota, Minneapolis, MN, USA. For more info, visit http://www.sph.umn.edu/academics/divisions/biostatistics/

Duties and Responsibilities

The post-doc will work with Dr. Wei Pan (https://directory.sph.umn.edu/bio/sph-a-z/wei-pan or http://www.biostat.umn.edu/~weip/), Dr. Xiaotong Shen (http://users.stat.umn.edu/~xshen/) and other collaborators in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning with GWAS/sequencing data and multiple types of omic/neuroimaging data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include software development (mostly in R, or in Python/TensorFlow/Keras/PyTorch for deep learning), possibly theory development, simulation studies, real data analysis, and writing manuscripts.

Position Qualifications

A PhD degree in Biostatistics, Statistics, Computer Science or a related field, strong computing/programming and communication skills, and previous research experience in (I) at least one of 1) statistical genetics/genomics/omics, 2) neuroimaging or medical imaging, and 3) machine learning/deep learning, and (II) a related topic (e.g. Big Data or computing) are required.