The department of Pathology is seeking a highly motivated Senior Bioinformatics Research Scientist to lead projects to dissect the underlying mechanisms for an uncommon but clinically important pediatric brain tumor called ependymoma. Dealing with large numbers of genomic and epigenomic datasets, including DNA methylation profiling, gene expression profiling and ChipSeq, you will be working with scientists from the lab of Dr. David Ellison. Candidates with a strong background in bioinformatics, computational biology, and cancer genomics are highly encouraged to apply for this position. You will not only be manipulating the data, but also visualizing data for presentations and publications. This role provides an exciting opportunity to solve challenging, but highly relevant, scientific questions with new methodologies such as ATAC-Seq, whole-genome bi-sulfite sequencing and single cell RNA-seq.
In this role, you will become an expert in both genomics and functional genomics by working in a highly collaborative environment. Specific responsibilities may involve developing and evaluating analytic tools and, through collaborative initiatives, machine-learning approaches for genomic analysis, communicating with our partners and users, project management, and manuscript preparation. You will work closely with members of our Computational Biology department, giving you access to high performance computing clusters, a cloud computing environment, innovative visualization tools, highly automated analytical pipelines and mentoring from faculty scientists with deep experience in data analysis, data management and delivery of high-quality results. Take the first step to join our team by applying now!
Ph.D. in Molecular Biology, Biochemistry, Computer Science, Statistics, Mathematics, Bioinformatics or related field required
Three (3) years of postdoctoral and/or job experience in Computational Biology or Bioinformatics research required with analytical experience in the following areas: sequencing data, microarrays, SNPs, proteomics data or biological pathways
Experience with programming languages such as Perl, C, C++, SQL, PHP or Java required
Experience in development of algorithms, statistical methods or scientific software is preferred
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