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Career Application:
Statistical Geneticist


Background:

Built over twenty years on the world’s largest collection of human genomes, WuXi NextCODE’s platform powers the biggest and most innovative precision medicine efforts on four continents, from pioneering population-optimized genome tests to providing wellness products. The customers we serve cover a broad spectrum, including clinicians, pharmaceutical companies, researchers and consumers who want to be more pro-active about their health management.

 

Job summary:

We are looking for a Statistical Geneticist with formal training in biostatistics, and experience using standard and developing new statistical methodology for genetic data (SNP genotype and NGS). The successful candidate will report to the Vice President of Statistical Sciences of WuXiNextCODE’s Advanced A.I. Research Laboratory and work with a diverse team of geneticists, bioinformaticians, computer and machine learning scientists, and computational statisticians within.. This person will apply established statistical tools and develop novel statistical approaches to analyze associations of millions of human genotypes and other omic data from WuXiNextCODE’s large sequencing initiatives. This person will provide statistical design expertise and data analyses for data derived from multi-cohort consortia, and will participate in preparation of manuscripts and presentations reporting study results. The successful candidate will be eager to develop novel statistical methods, become proficient in the GORquery language underlying the WuXiNextCODE platform for large datasets, and analyze and integrate different data sources to provide meaningful genomic discoveries.

 

Requirements:

  • M.S. or Ph.D. in Statistics, Biostatistics, Statistical Genetics, or related field
  • Understanding of theoretical and applied statistics related to meta-analysis of large human genetic studies
  • Demonstrated experience refining established or developing novel statistical methods to analyze large-scale omics data
  • Research experience in one or more of the following areas: genome-wide association studies, linkage studies, and admixture mapping in diverse human populations
  • Experience with genetic data manipulation, annotation and imputation
  • Experience writing reports, posters, and manuscripts, including interpretation of analysis results and descriptions of statistical methodologies
  • Working Proficiency of Python and/or R in a Linux environment required
  • Excellent interpersonal, verbal and written communication skills required