Bioinformatics Analyst I​/II

Overview

Fred Hutchinson Cancer Center is an independent, non-profit 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 Fong lab is seeking a highly qualified and motivated Bioinformatics Analyst to work in a collaborative environment leading research on the mechanisms of cancer immunotherapy response and resistance. The focus of our lab is to unravel the dynamic interactions governing the generation of anti-tumor immunity and apply this knowledge toward developing novel approaches for the study and treatment of cancer.

We are searching for an analyst with an interest in developing pipelines for quality control and end-to-end analysis including data visualization of a variety of datasets.

A cover letter is required with your application detailing your interest in this position.

• Implement, apply, and evaluate tools to process, integrate, batch-correct and visualize genomics datasets (single-cell RNA‑seq, Bulk RNA‑seq, CITE‑seq), multiparametric flow cytometry datasets, multiplexed cytokine/protein datasets.
• Interpret the data and explain the results in research discussions with experimental collaborators.
• Perform quality control and end-to-end analysis of large sequence datasets from diverse workflows.
• Identify best‑practice bioinformatics tools and strategies to meet the needs of proposed projects.
• Provide figures and written sections describing methods and results for manuscripts, presentations, and grant applications.
• Ensure integrity and consistency of primary data, track experimental methods and metadata, define standardized analysis pipelines.
• Ability to learn new tools and content quickly and independently (although training will be given for specific types of analysis performed in the lab).
• Other duties as assigned.

A cover letter is required to be considered for this position.

Minimum Qualifications

• BS degree in Biology, Statistics, Computer Science 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, Node, or C++).

• 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…