Bioinformatics Analyst I​/II

Overview

Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers.

Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality. At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect.

Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems.

The Ghajar Lab at the Fred Hutchinson Cancer Center is searching for a computational scientist with a passion for innovating computational approaches to address some of the most fundamental questions in single cell biology and cancer pathogenesis/metastasis.

A computational scientist position (full-time/fully in-person) at the Bioinformatics Analyst I/II level is available immediately within The Laboratory for the Study of Metastatic Microenvironments , led by Cyrus Ghajar. The successful candidate will utilize a first-of-its-kind resource of primary tumor-derived whole genome sequencing data and single cell RNA sequencing data – paired with single cell RNA sequencing data from matched bone marrow – to build pipelines capable of uncovering clonal and phylogenetic relationships between tumor and immune cells in the breast, blood, and bone marrow.

They will use these data towards hypothesis-generating biological insights. To do so, they will work closely with members of the Ghajar Laboratory to generate ideal tissue specimens, profile them using state-of-the-art approaches, and to design follow-up experiments in metastasis models. They will innovate (not simply apply) computational methods to analyze single cell data, and to visualize these data. And, they will contribute significantly to the development of publications and funding applications showcasing this work.

The ideal candidate will have a Masters or PhD in bioinformatics, computational biology, genetics, data science, statistics, or related field. They will have extensive experience programming in R and/or Python. And they will apply this expertise to build upon existing computational tools – and invent others – to analyze an array of features present in single cell data sets. They will be adept at displaying these data in an intuitive and artful manner.

They will generate theories and testable hypotheses based on these data, and help guide follow-up studies to answer what we view as some of the most fundamentally important questions in cell biology.

• 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…