Please contact your Administrator to change your authorization settings.
| Job ID | 27082 | Type | Regular Full-Time | Location | US-WA-Seattle | Category | Biostatistics, Bioinformatics and Computational Biology |
The Ghajar Lab at Fred Hutchinson Cancer Center is searching for a computational scientist with a passion for applying and innovating single cell and spatial biology approaches to address some of the most fundamental questions in cell biology and cancer pathogenesis.
A computational scientist position (full-time/fully in-person) at the Bioinformatics Analyst II level is available immediately within The Laboratory for the Study of Metastatic Microenvironments, led by Cyrus Ghajar. The successful candidate will build novel pipelines to uncover clonal and phylogenetic relationships between primary breast tumors and their disseminated seeds. They will launch a new research endeavor focused on entirely on the application of spatial transcriptomics to enumerate , define and transform cellular microenvironments - or niches - within tissues. To do so, they will work closely with members of the Ghajar Laboratory to generate ideal tissue specimens, and profile them using state-of-the-art approaches. They will innovate (not simply apply) computational methods to analyze single cell and spatial transcriptomic data, and to visualize these data. And, they will contribute significantly to publications and funding applications showcasing this work.
The ideal candidate will have a PhD in bioinformatics, computational biology, genetics, data science 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 tissue-scale, cellular and subcellular features present in single cell and spatial transcriptomic data sets. They will be adept at displaying these data in an intuitive an artful manner. They will also 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.
This role will be 100% onsite at our Seattle South Lake Union campus.
- Analyze tissue scale spatial transcriptomic datasets spanning liver, brain, bone marrow and other normal and disseminated tumor cell bearing tissues. Trial multiple workflows and develop custom models to characterize niches, niche constituents, and niche occupancy based on protein and transcript expression.
- Adopt and develop data visualization approaches necessary to display single cell transcriptomic and spatial data thoughtfully and intuitively.
- Partner with researchers to shape the best experiments and conditions to generate data from, and to test hypotheses shaped by these data.
- 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. Provide training and support as lab members analyze and interpret results.
- Master's degree in bioinformatics, computational biology, genetics, data science or related field with at least three years' direct experience in computational analysis of large single cell sequencing-based molecular data sets.
- Direct experience can include phylogenetic analysis of evolution on a cellular scale, analysis of single cell RNA-seq data with multiple contrasts, development of custom data visualization approaches, analysis of single cell multi-ome data, integration of data across multiple modalities (e.g., epigenetic profiling and RNA-seq), and so forth.
- Proficiency in R and/or Python is essential.
- Familiarity with commonly used Bioconductor packages.
- Demonstrated ability to generate and customize common data visualizations (UMAP/t-SNE, volcano plots, Circos plots, etc).
- Excellent written and verbal communication skills are absolutely required.
- Ability to learn new tools and content quickly and independently.
- Ability to work independently and in a team.
PREFERRED QUALIFICATIONS:
- PhD in bioinformatics, computational biology, genetics, data science or related field
- Some exposure to and analysis of high-dimensional spatial data sets.
A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and antiracism in your career or that will be made through your work at Fred Hutch is requested of all finalists.
The annual base salary range for this position is from $76,606 to $114,878, and pay offered will be based on experience and qualifications. This position may be eligible for relocation assistance.
Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include 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), and partially paid sabbatical leave (up to 6 months).