Research - Laboratory/Non-Laboratory, Staff/Administrative
Post-doctoral Associate in Statistical Genetics/Omics or Deep Learning in the Division of Biostatistics, University of Minnesota
Multiple post-doc positions are available now (until filled) in the Division of Biostatistics at the University of Minnesota, Minneapolis, MN, USA. For more info, visit http://www.sph.umn.edu/academics/divisions/biostatistics/
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/) and his collaborators within and outside the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for association analysis and causal inference with GWAS/sequencing data, including integrative analysis of multiple types of omic/neuroimaging data, such as TWAS and IWAS. The candidate is also encouraged to expand or focus his/her research to/on deep learning for GWAS, omic and neuroimaging data. In addition to new methods development and evaluations, the job responsibilities include new methods and software development (mostly in R, or in Python/TensorFlow/Keras/PyTorch for deep learning) and documentation (60%), real data analysis for cardiovascular diseases and Alzheimer’s disease (30%), and others (10%).
The positions are available immediately, and will remain open until filled. Each appointment is annually renewable for two years, possibly extendable to year 3, conditional on satisfactory performance and funding availability.
Qualifications: A PhD degree in Biostatistics, Statistics, Bioinformatics, Computer Science or a related field, strong computing/programming and communication skills, and interest in statistical genetics/genomics or Big Data/deep learning are required. Experience in statistical genetics and/or Big Data/deep learning is preferred, but not required.
Internal Number: 335522
About University of Minnesota, Twin Cities
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.