Bioinformatics Analyst I/II
- Seattle, WA
- $77,976-102,211 per year
- Permanent
- Full-time
- 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.
Bioinformatics Analyst I
- 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++).
- Experience with R and statistical analysis.
- Knowledge of bulk and single cell RNA-seq datasets and analysis methods.
- Familiarity with cancer immunotherapy research or related biological domains.
- Experience with data pipeline development and workflow management.
- Proficiency with Linux/Unix shell scripting (e.g., bash).
- Familiarity with cloud servers or high-performance computing resources.
- Ability to generate and customize visualizations.
- Strong organizational skills, including the ability to manage and prioritize multiple competing tasks.
- Good communication skills and an interest in learning.
- Ability to work independently and in a team.
- Scientific curiosity.
- 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).