Requires a PhD in biological sciences, bioinformatics, computer science, engineering or mathematics, or a related field and a minimum of 3 years of postdoctoral training in bioinformatics, or an equivalent combination of education, training and experience from which comparable knowledge, skills and abilities have been attained. The ideal candidate should have two years of relevant recent experience with providing user support in a core/academic setting. Preference will be given to those candidates who have experience in clinical genomics and biomarker discovery related data analysis.
The candidate should have experience analyzing high-throughput genomic datasets derived from next-generation sequencing and expression array technologies, as well as thorough knowledge of the standard software packages used for these purposes. The knowledge of at least one programming language (C/C++, Perl, Python, or Ruby) and of at least one environment for high-dimensional data analysis (SAS, R/Bioconductor, or Matlab) is required.
Expertise in the analyzing high-dimensional data (-omics data) using machine learning/data mining techniques is preferred. Preference will be given to candidates who have high level understanding of both molecular biology, clinical genomics and cutting-edge genomic technologies with outstanding professional track records of collaborative investigation.
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