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Computational Spatial Transcriptomics Jobs in Seattle, WA

This position is engaged in the field of Spatial transcriptomics and bioinformatics. This position ... Bachelor's degree in Bioinformatics, Computational Biology, Biostatistics, Data Science or a ...

Computational biology/bioinformatics with emphasis on spatial transcriptomics, proteomics, and immunosequencing using Pixelseq and an immune receptorfocused multimodal expansion ("ImmunoPixelseq"

Computational Spatial Transcriptomics information

See Seattle, WA salary details

$46

$62

$84

How much do computational spatial transcriptomics jobs pay per hour?

As of May 28, 2026, the average hourly pay for computational spatial transcriptomics in Seattle, WA is $62.51, according to ZipRecruiter salary data. Most workers in this role earn between $53.37 and $83.70 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Spatial Transcriptomics Scientist, and why are they important?

To excel in Computational Spatial Transcriptomics, you need a strong background in bioinformatics, genomics, and statistical data analysis, typically supported by advanced degrees in computational biology or related fields. Familiarity with programming languages (such as R and Python), spatial transcriptomics platforms (like 10x Genomics Visium), and high-throughput sequencing data analysis tools is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These competencies ensure accurate data interpretation, innovative research, and successful integration of spatial transcriptomics insights into biological and clinical applications.

What are some typical challenges faced when working in computational spatial transcriptomics, and how can new team members prepare for them?

Professionals in computational spatial transcriptomics often encounter challenges related to handling and analyzing large, complex datasets that combine spatial and gene expression information. Integrating data from different technologies and ensuring data quality can be demanding, requiring strong programming skills and familiarity with bioinformatics pipelines. New team members can prepare by strengthening their skills in statistical analysis, programming languages like Python or R, and staying updated on the latest spatial transcriptomics techniques. Collaborating closely with experimental biologists and data scientists is also key to overcoming these challenges and driving successful research outcomes.

What is computational spatial transcriptomics?

Computational spatial transcriptomics is a field that combines advanced computational methods with spatial transcriptomics, a technique that measures gene expression within the physical context of tissue samples. It involves processing and analyzing large datasets to map where specific genes are active within tissues, helping researchers understand how cells interact and function in their native environments. This approach is crucial for studies in developmental biology, cancer research, and neuroscience, as it provides insights into cellular organization and tissue architecture. Computational tools help extract meaningful patterns from complex data, enabling discoveries that were previously impossible with traditional methods.

What is the difference between Computational Spatial Transcriptomics vs Computational Biologist?

AspectComputational Spatial TranscriptomicsComputational Biologist
Required CredentialsAdvanced degrees in bioinformatics, computational biology, or related fields; experience with spatial data analysisTypically a PhD or Master's in biology, bioinformatics, or related disciplines; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic institutions focusing on spatial genomicsResearch institutions, biotech firms, academia working on biological data analysis
Industry UsageSpecialized in spatial transcriptomics techniques and data interpretationBroad biological data analysis across various fields

Computational Spatial Transcriptomics focuses on analyzing spatial gene expression data within tissues, requiring specialized skills in spatial data processing. In contrast, Computational Biologists work on a wider range of biological data types. While both roles involve bioinformatics expertise, the former emphasizes spatial data analysis techniques specific to transcriptomics.

What are popular job titles related to Computational Spatial Transcriptomics jobs in Seattle, WA? For Computational Spatial Transcriptomics jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Computational Spatial Transcriptomics jobs in Seattle, WA look for? The top searched job categories for Computational Spatial Transcriptomics jobs in Seattle, WA are:
Infographic showing various Computational Spatial Transcriptomics job openings in Seattle, WA as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $130,019 per year, or $62.5 per hour.
Research Scientist/Engineer 3

Research Scientist/Engineer 3

Uw

Seattle, WA • On-site

Full-time

Posted 7 days ago


University Of Washington rating

8.4

Company rating: 8.4 out of 10

Based on 85 frontline employees who took The Breakroom Quiz

73rd of 528 rated colleges and universities


Job description

Job Description

The Division of Metabolism, Endocrinology and Nutrition (MET) has an outstanding opportunity for a Research Scientist/Engineer 3 position to support studies within the Pyle and Bjornstad Laboratories.

Housed within the University of Washington Medicine Diabetes Institute at the South Lake Union campus, the Pyle laboratory applies translationaldatascience to bridge complexbiostatistics andbioinformatics findings into medical insights. The Bjornstad and Pylelaboratories focus on metabolic and hemodynamic mechanisms underlying the development of diabetic kidney disease (DKD) and cardiovascular disease (CVD) in Type 1 (T1D) and Type 2 (T2D) diabetes and obesity.

This position is engaged in the field of Spatial transcriptomics and bioinformatics. This position supports the analysis of spatial transcriptomic data generated from kidney biopsy tissue using 10x Genomics platforms including Visium, Visium HD, and Xenium Prime 5K. The role involves processing, quality control, and interpretation of spatially resolved gene expression data to understand disease mechanisms in diabetic kidney disease and obesity-related kidney disease. A key focus includes cell type deconvolution, integration with single-cell RNA-seq reference data, identification of spatially variable genes, and pathway enrichment analysis. This position requires effective communication of results through manuscript writing and presentations at conferences. This position will work under general guidance, receiving instruction on specific assignment objectives, and will collaborate with investigators on spatial transcriptomic analyses, data visualization, and preparation of abstracts, talks, and manuscripts.

Research Sponsors/Stakeholders: Novo Nordisk and NIH

DUTIES AND RESPONSIBILITIES

Spatial Transcriptomics and Data Analysis 60%

Process and quality-control 10x Genomics Visium, Visium HD, and Xenium Prime 5K spatial transcriptomics data from human and mouse kidney tissue

Perform spatial preprocessing with Space Ranger and downstream integration across samples using Seurat and BPCells

Perform cell type deconvolution and mapping by integrating spatial data with single-cell RNA-seq reference objects using RCTD (spacexr) workflow

Identify spatially variable genes and cluster-specific markers to prioritize biological pathways and candidate genes for downstream investigation

Perform differential expression and pathway enrichment analysis using decoupleR, clusterProfiler, and GSEA

Perform image stitching and alignment using ImageJ and Loupe Browser for spatial preprocessing

Integrate multi-sample spatial datasets to enable scalable normalization, clustering, and cross-sample comparison

Develop protocol-specific systems and documents including process flows, training manuals, and Standard Operating Procedures (SOPs).

Maintain subject level documentation and prepares documents, equipment and/or supplies

Provide the biostatistical/data science expertise and leadership in study design, study oversight, data management, data analysis and manuscript preparation to assist all levels of biomedical investigators and clinicians on new research activities across a wide range of disciplines

Provide mentorship to collaborators, trainees, and team members

Acts as a subject matter expert and authority in the areas of data management and data analysis

Serve as an expert resource to PIs and other stakeholders

Bioinformatics Programming 20%

Assist with the design and development of major bioinformatics-related programming projects

Write custom scripts to access databases, analyze data, and create reproducible visual representations of results

Write custom web tools for PIs and other stakeholders

Laboratory support 20%

Collaborate on the preparation and presentation of data for publications in peer-reviewed journals, ensuring clarity and adherence to publication standards.

Assist Team Leads, Supervisors, and management in developing and implementing effective processes, procedures, and quality improvement initiatives that enhance team performance.

Develop and disseminate a variety of tools designed to access relevant clinical and sample data

Provide guidance and training to junior team members, fostering a culture of continuous learning and professional development.

Identify and analyze operational efficiency issues, communicating findings and recommendations to leadership for informed decision-making.

Proactively identify and recommend training and development opportunities for both new hires and existing team members to enhance skill sets and performance.

Provides input and feedback to leadership on team members' overall performance, opportunities for development, and process improvement initiatives

MINIMUM QUALIFICATIONS

  • Bachelor's degree in Bioinformatics, Computational Biology, Biostatistics, Data Science or a related field and four years of relevant experience.

Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements, such as a license, certification, and/or registration.

ADDITIONAL REQUIREMENTS

Advanced knowledge of basic statistical principles relevant in medical research

Experience with spatial transcriptomics platforms (10x Genomics Visium, Visium HD, and/or Xenium)

Ability to analyze and solve complex problems and apply quantitative analytical approaches

Demonstrated fluency in one or more programming languages (e.g., R, Python, Perl, Java, C++) and willingness to learn new programming languages as necessary

Familiarity with statistical analytical concepts and methods

Ability to communicate effectively, both in writing and orally

Ability to establish and maintain effective working relationships with employees at all levels throughout the institution

Outstanding customer service skills

Demonstrated commitment and leadership ability to advance diversity and inclusion

Knowledge of basic human anatomy, physiology medical terminology

Ability to interpret and master complex research protocol information

Ability to handle multiple projects simultaneously within rigorous timelines

Potential to work independently with minimal supervision and in a team atmosphere

DESIRED QUALIFICATIONS

Experience with 10x Genomics Xenium Prime 5K spatial transcriptomics platform

Experience with single-cell RNA-seq analysis and integration with spatial data (Seurat, spacexr/RCTD)

#UWDeptMedicineJobs

Compensation, Benefits and Position Details

Pay Range Minimum:

$80,244.00 annual

Pay Range Maximum:

$132,612.00 annual

Other Compensation:

-

Benefits:

For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/

Shift:

First Shift (United States of America)

Temporary or Regular?

This is a regular position

FTE (Full-Time Equivalent):

100.00%

Union/Bargaining Unit:

UAW Research

About the UW

Working at the University of Washington provides a unique opportunity to change lives - on our campuses, in our state and around the world.

UW employees bring their boundless energy, creative problem-solving skills and dedication to building stronger minds and a healthier world. In return, they enjoy outstanding benefits, opportunities for professional growth and the chance to work in an environment known for its diversity, intellectual excitement, artistic pursuits and natural beauty.

Our Commitment

The University of Washington is committed to fostering an inclusive, respectful and welcoming community for all. As an equal opportunity employer, the University considers applicants for employment without regard to race, color, creed, religion, national origin, citizenship, sex, pregnancy, age, marital status, sexual orientation, gender identity or expression, genetic information, disability, or veteran status consistent with UW Executive Order No. 81.

To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or dso@uw.edu.

Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.


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