"Bioinformatics Analyst 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 Bioinformatics Analyst II provide highly specialized consulting and data analysis services to researchers at the Hutch and across the wider Fred Hutch/UW Cancer Consortium. This position requires the ability to work independently, manage multiple overlapping demands, and communicate effectively with faculty, and research staff on a wide range of topics in biology, and data science.

The Loeb lab at the Fred Hutch has an opening for a temporary and part time computational scientist with experience in spatial and genomic data analysis. This position will work with members of the Laboratory of Dr. Keith Loeb and Dr. Nick Petty in the division of Translational Sciences and Therapeutics to help analysis data relating to the characterization of donor cells that have engrafted into the brains of stem cell transplant recipients. Prior studies in model organisms and humans have shown that a distinct population of macrophages enter and engraft into the brain following a stem cell transplant. Studies in model organism have shown that these cells are similar to endogenous microglia and have the potential to be used in cell and genetic therapy for a number of metabolic and neurodegenerative conditions. The position centers on the analysis and integration of spatial multi-omics datasets, particularly those generated using 10x Genomics Xenium in situ transcriptomics, single cell/single nuclei RNA and ATAC sequencing, RNA in situ hybridization studies.

Responsibilities

• Process, analyze, and interpret spatial transcriptomics and spatial proteomics data focusing on the identification and characterization of rare donor derived cells.
• Develop and implement computational workflows for image alignment, cell segmentation, gene/protein quantification, clustering, and spatial domain detection.
• Compare the transcriptomics of donor derived cells to endogenous microglia to determine unique aspects of the donor derived cells and predict the capacity of the donor derived cell to functionally replace endogenous microglia.
• Develop methods to analyze the spatial data to determine the cellular neighborhood of the donor derived cells and how they influence adjacent cells.
• Collaborate with lab members and collaborators on study design, data interpretation, and presentation of results. A key aspect of the position is to help educate others in the group to facilitate future studies.
• Generate high-quality visualizations and figures for internal reports, manuscripts, and grant submissions.
• Maintain documentation, reproducibility, and version control of analysis pipelines (GitHub, Jupyter/R Markdown, Snakemake/Nextflow).
• Participate in lab meetings, contribute to collaborative problem solving, and stay current with emerging computational methods in spatial and single-cell biology.

Qualifications

MINIMUM QUALIFICATIONS:

• 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:

• Familiarity with workflow and scheduling software (e.g. Slurm).
• Excellent written and verbal communication skills are absolutely required.

The hourly pay range for this position is from $38.69 to $58.02 and pay offered will be based on experience and qualifications.

This position is not eligible for H-1B sponsorship at this time.

Fred Hutchinson Cancer Center offers employees access to a retirement savings plan, an employee assistance program, paid sick leave (1 hour for every 30 hours worked), and prorated paid holidays (up to 11 days per year).