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The successful candidate will work with a diverse group of technical staff and bioinformatics specialists to support the wide ranging genomics data analysis needs of Fred Hutch faculty and staff. The Bioinformatics Analyst will report to the Bioinformatics Shared Resource Manager, in association with the Director of the Genomics and Bioinformatics Shared Resources, and will work with Fred Hutch scientists to refine computational research questions and develop analytical processes that can be applied to genomics datasets.
- Work closely with Genomics staff to bring new instrumentation online, implement new analysis workflows, and maintain laboratory operations including automation of routine data processing and routing to end-users.
- Develop, implement, and test standardized analytical pipelines to support common NextGen sequencing assays (e.g., RNAseq, ChIPseq, SNV/CNV).
- Communicate with researchers and identify appropriate bioinformatics tools to meet the needs of proposed research projects.
- Provide support to Fred Hutch statisticians, bioinformaticians, and computational biologists working with genomics data.
- Participate in weekly staff meeting to discuss ongoing projects andprovide advice and support to colleagues. Provide figures & written sections describing methods and results for manuscripts, presentations, and grant applications generated by Fred Hutch researchers.
Individual will have a bachelor's, master's or PhD degree in computer science, bioinformatics, biology, genetics, or related discipline with significant computational emphasis and at least 3 years of relevant experience working with genomics data. The individual must be proficient with Linux/Unix shell scripting (primarily bash) and possess strong programming skills in Python and R. Knowledge of Java or C++ a plus. Must have a proven track record of deep sequencing analysis showing a working knowledge of standard analysis tools (e.g., GATK variant calling pipelines, alignment & pseudoalignment based RNA-seq quantitation, Bioconductor packages) and relevant databases. The individual should be self-motivated, perform in a highly independent manner, and possess strong interest in the biological sciences. Solid communication skills (both verbal and written) and organizational skills are essential, as is the ability to be creative in problem-solving situations.
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