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 software development (mostly in R, or in Python/TensorFlow/Keras/PyTorch for deep learning), simulation studies, real data analysis, and writing manuscripts.
The annually renewable appointment is for 1-2 years, possibly extendable to year 3, conditional on satisfactory performance and funding availability.
For preliminary inquiries, you may send your CV to firstname.lastname@example.org
Questions? Inquiries are welcome and should be directed to Dr. Wei Pan by email at email@example.com
The University of Minnesota offers a comprehensive benefits package including:
· Competitive wages, paid holidays, vacation and sick leave · Low cost medical, dental, and pharmacy plans · Health care and dependent daycare flexible spending accounts · Excellent retirement plans with employer match · Disability and employer paid life insurance · Wellbeing program with reduced insurance premiums · Tuition reimbursement opportunities covering 75%-100% of eligible tuition · Student loan forgiveness opportunity · Opportunities for growth and promotion · Employee Assistance Program
Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field, strong computing/programming and communication skills, and strong interest in statistical genetics/genomics and/or Big Data/deep learning are required. Experience in statistical genetics and/or Big Data/deep learning is preferred.
Internal Number: 339104
About University of Minnesota, Twin Cities
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