Postdoctoral Fellow

Colorado State University • Fort Collins, CO

2d • Hybrid

About The Position

Dr. Tianying Wang in the Department of Statistics at Colorado State University invites applications for two postdoctoral positions in statistical genetics and genomics. The fellow will have the opportunity to work closely with Dr. Gao Wang and his research team in the Department of Neurology at Columbia University. The postdoctoral fellow will work closely with both investigators in a collaborative research environment spanning statistical methodology, statistical genetics, functional genomics, and neuroscience. The research program includes NIH-funded work on developing statistical methods to study nonlinear and context-dependent genetic regulation in Alzheimer’s disease and the aging brain, as well as related research in statistical genetics and functional genomics. The position offers opportunities to develop new statistical methods, analyze large-scale human genetic and multi-omic data, lead methodological and applied projects, and develop an independent research direction within the broader scientific scope of the program. The position is expected to be supported for two years, with the possibility of extension based on satisfactory performance, funding availability, and mutual interest. Work authorization visa sponsorship may be available based on the specific situation, including cost, for the selected final candidate.

Requirements

• Ph.D. in statistics, biostatistics, statistical genetics, bioinformatics, computational biology, or a closely related quantitative field, completed by the start of the appointment.
• Proficiency in R.
• Strong statistical training or substantive experience analyzing human genetic or genomic data.

Nice To Haves

• Experience developing statistical methods for genetic or genomic studies.
• Experience in one or more of the following: genetic association analysis, fine-mapping, xQTL analysis, colocalization, TWAS, or genetic and multi-omic data integration.
• Experience with reproducible scientific computing, documented software, or Linux/HPC computing.
• Ability to communicate research findings clearly through scientific writing or presentations.
• Candidates need not have experience in every listed method or data type.

Responsibilities

• Develop statistical methods for genetic association and functional genomics, including quantile-based analysis, fine-mapping, xQTL analysis, colocalization, or TWAS, according to project needs and research fit.
• Conduct data quality assessment and analyze human genetic, genomic, and multi-omic data.
• Design and conduct simulation studies to evaluate statistical methods and interpret their finite-sample properties.
• Develop, test, and document statistical software and reproducible analyses in R, with other languages as appropriate.
• Lead preparation of manuscripts, figures, and presentations and communicate findings to collaborators.
• Work with the supervisor to define research questions, interpret results, and develop an independent research direction.
• Follow applicable data access and confidentiality requirements.

Benefits

• Robust benefits package
• Collaborative atmosphere
• Focus on work-life balance
• Work authorization visa sponsorship may be available

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree