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University of Minnesota

Post-Doctoral Associate (# 376558)

Closes:

Salary: $63,480 – $64,380 per year

56
Job ID: 376558

About the Job

Our research team in the Division of Epidemiology and Clinical Research (Pediatrics, Medical School) and Division of Biostatistics and Health Data Science (School of Public Health) invites qualified individuals to apply for a post-doctoral position to conduct multidisciplinary research in pediatric cancer epidemiology and statistical genetics. The position is a one-year, full-time role that is renewable for up to two additional years, contingent upon performance, and is supported by federal National Cancer Institute (NCI) funding. Dedicated multidisciplinary mentorship will be provided by a molecular/genetic epidemiologist (Cindy Im, PhD, Associate Professor) and two statistical geneticists (Saonli Basu, PhD, Professor; Tianzhong Yang, PhD, Assistant Professor). The postdoctoral scholar will have the opportunity to lead multiple projects involving cutting-edge genetic/genomic analyses of childhood cancer risk with novel large-scale deep-coverage whole-genome/exome sequencing datasets. Specifically, we expect the scholar to lead/contribute to manuscripts summarizing applied work (GWAS, rare variant association analysis, multi-ancestry analysis) and/or methods development (heritability estimation; pleiotropic [multiple trait] association analysis). Career development opportunities, including initiating new independent research projects and developing/applying for grants (K99/R00), will be prioritized.

100%: Participate in the deign, implementation, and evaluation of research. Collect and analyze data. Participate in preparing and presenting data to investigators and disseminating results to

professional audiences. Author or co-author manuscripts, reports, grants, and papers.

Qualifications

Required Qualifications:
  • PhD in epidemiology, biostatistics, data science, or a relevant field
  • Proven research experience with analysis of large-scale genetic/genomic datasets and/or statistical programming languages commonly used in high-dimensional analyses (e.g., R, Python)

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