Bioinformatics Analyst I/II at Fred Hutch in Seattle, WA

Summary: Fred Hutchinson Cancer Center is an independent, nonprofit organization focused on cancer and infectious diseases. The Ghajar Lab is seeking a computational scientist to innovate computational approaches for analyzing single cell data related to cancer biology and metastasis, utilizing advanced sequencing data to generate biological insights. Responsibilities: - Conduct integrative analysis of bulk and single cell tumor datasets, using genetic signatures to establish clonal relationships between the primary tumor and its disseminated seeds - Pioneer the conduct and benchmark analysis of single cell DNA+RNA sequencing to establish these relationships - Conduct analysis of TCR and BCR sequencing in tumors, blood, and bone marrow to examine clonal dynamics before and after treatment - Adopt and develop data visualization approaches necessary to display single cell transcriptomic and spatial data thoughtfully and intuitively - Provide figures and written sections to document methods and results for manuscripts, presentations, and grant applications - Conduct best programming practices such as version control, annotation, data organization, etc, and work towards standardized analysis pipelines for the laboratory - All responsibilities of the Bioinformatics Analyst I with a higher level of autonomy - Provide training and support as lab members analyze and interpret results - Partner with researchers to shape the best experiments and conditions to generate data from, and to test hypotheses shaped by these data Required Qualifications: - Bachelor's degree in Statistics, Biostatistics, Bioinformatics or equivalent education - 0-2 years of work experience with bioinformatics in the relevant scientific domain - Proficiency in, at least, one modern scripting or programming language (Python, R, etc) - Bachelor's degree in bioinformatics, computational biology, genetics, or related field with at least three years' direct experience in computational analysis of large sequence-based molecular data sets - Direct experience must include best-practice germline & somatic variant calling from exome capture data, analysis of bulk RNA-seq data with multiple contrasts, analysis of multimodal single-cell profiling data, epigenetic profiling, gene set enrichment, and integration of data across multiple modalities (e.g., epigenetic profiling and RNA-seq) - Effective use of shell scripting and significant fluency in R and Python 3 are essential - Facility with commonly used Bioconductor packages, ggplot, tidyverse etc - Ability to generate and customize common data visualizations (PCA plots, volcano plots, Circos plots, etc) Preferred Qualifications: - PHD degree in Statistics, Biostatistics, Bioinformatics or equivalent education - Demonstrated ability to conduct genomic analyses, evidenced by contributing authorship(s) on peer-reviewed publication(s) - Excellent written and verbal communication skills - Good numeracy, literacy, and organizational skills Required Skills: Bioinformatics, R programming, Python programming Important Skills: Data visualization, Genomic analysis, Statistical analysis Benefits: Medical/vision, Dental, Flexible spending accounts, Life, Disability, Retirement, Family life support, Employee assistance program, Onsite health clinic, Tuition reimbursement, Paid vacation (12-22 days per year), Paid sick leave (12-25 days per year), Paid holidays (13 days per year), Paid parental leave (up to 4 weeks)