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Spatial Transcriptomics Jobs in San Francisco, CA

Valius Sciences

Computational Biologist

San Francisco, CA · On-site

$140 - $200/hr

Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read sequencing, to derive meaningful insights from complex patient datasets. * Deliver patient-facing results.

Valius Sciences

Computational Biologist

San Francisco, CA · On-site

$125K - $185K/yr

Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read sequencing, to derive meaningful insights from complex patient datasets. * Deliver patient-facing results.

Nudge

Histotechnologist

San Francisco, CA · On-site

Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...

nudge

Histotechnologist

San Francisco, CA · On-site

Prepare and process samples for spatial omics platforms, including multiplexed protein imaging and spatial transcriptomics, with both RNA- and protein-based tagging approaches * Develop, optimize ...

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All JobsSpatial Transcriptomics JobsSpatial Transcriptomics Jobs in San Francisco, CA

Spatial Transcriptomics information

See San Francisco, CA salary details

$57.7K

$239.7K

$471.3K

How much do spatial transcriptomics jobs pay per year?

As of Sep 6, 2026, the average yearly pay for spatial transcriptomics in San Francisco, CA is $239,720.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,500.00 and $471,300.00 per year, depending on experience, location, and employer.

What is spatial transcriptomics?

Spatial transcriptomics is an advanced technique that allows scientists to measure gene expression within the spatial context of tissue samples. Unlike traditional RNA sequencing, which loses information about where each gene is expressed, spatial transcriptomics preserves the physical location of gene activity in tissues. This helps researchers better understand how cells function within their native environments and interact with neighboring cells, which is especially valuable in fields like cancer research, neuroscience, and developmental biology. The method combines microscopy, molecular biology, and computational analysis to produce detailed maps of gene expression.

What are the key skills and qualifications needed to thrive as a spatial transcriptomics scientist?

To thrive as a Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a life science field. Familiarity with spatial transcriptomics platforms (such as 10x Genomics Visium), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating on interdisciplinary research projects. These skills and qualities are crucial for generating high-quality spatial gene expression data and translating findings into meaningful biological insights.

What are some common challenges faced by professionals working in spatial transcriptomics, and how can they be addressed?

Professionals in spatial transcriptomics often encounter challenges related to handling large, complex datasets and integrating spatial information with gene expression data. Ensuring high-quality sample preparation and mastering advanced imaging or sequencing technologies are also frequent hurdles. These challenges can be addressed by collaborating closely with multidisciplinary teams—including bioinformaticians, molecular biologists, and imaging specialists—and staying up-to-date with the latest software tools and protocols. Continuous learning and effective communication within the team are key to overcoming technical and analytical obstacles in this rapidly evolving field.

What are popular job titles related to Spatial Transcriptomics jobs in San Francisco, CA?

For Spatial Transcriptomics jobs in San Francisco, CA, the most frequently searched job titles are:

What job categories do people searching Spatial Transcriptomics jobs in San Francisco, CA look for?

The top searched job categories for Spatial Transcriptomics jobs in San Francisco, CA are:

What cities near San Francisco, CA are hiring for Spatial Transcriptomics jobs?

Cities near San Francisco, CA with the most Spatial Transcriptomics job openings:

Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in San Francisco, CA as of August 2026, with employment types broken down into 75% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 75% Physical, 2% Hybrid, and 23% Remote job distribution, with an average salary of $239,720 per year, or $115.2 per hour.

Principal Scientist, Bioinformatics

Nkarta, Inc.

South San Francisco, CA • Hybrid

Full-time

Re-posted 23 days ago

Job description

Overview

Nkarta is seeking a highly motivated, collaborative, detail-oriented Principal Scientist to join our Translational Medicine team. This is a high-impact, hands-on leadership role for a senior bioinformatics scientist. The successful candidate will have deep expertise in single-cell and spatial omics technologies, along with experience in functional genomics and leading computational biology and/or bioinformatics programs in a biotech or pharmaceutical setting.

This individual will work collaboratively within Translational Medicine and cross-functionally to advance, support, and execute biomarker discovery, mechanism-of-action (MOA) investigations, and translational data analysis from clinical samples. A central focus of this role is to drive and execute on Nkarta's strategy for single-cell and spatial transcriptomics, leveraging scRNA-seq, spatial, and functional genomics approaches to drive translational insights, biomarker development, and clinical decision-making in early development.

Responsibilities

  • Lead and actively participate in the design and execution of computational strategies and hands-on analysis of clinical and biological datasets to support go/no-go decisions
  • Hands-on development and application of computational methods for single-cell and spatial transcriptomics to generate actionable translational insights from clinical samples
  • Establish scalable pipelines for multi-modal data integration across programs
  • Integrate and analyze functional genomics datasets (e.g., bulk RNA-seq) to generate mechanistic insights that inform translational and clinical strategies
  • Provide high-impact analyses with direct influence on clinical decision-making and visibility to senior leadership
  • Collaborate with senior leadership to define priorities, allocate resouces, and establish timelines aligned with company objectives
  • Partner with experimental scientists to design studies leveraging advanced omics approaches and interpret results
  • Ensure reproducibility, scalability, and data quality across bioinformatics pipelines
  • Communicate complex findings effectively to scientific and non-scientific stakeholders, including senior leadership

Qualifications

  • Deep expertise in single-cell and spatial transcriptomics analysis, including scRNA-seq and related high-dimensional omics datasets
  • Strong experience analyzing functional genomics and transcriptomic data (e.g., bulk RNA-seq, WES) to derive biological and translational insights
  • Strong foundation in biological sciences, with experience or interest in immunology and disease biology
  • Deep understanding of modern statistical and computational methods for high-dimensional data analysis
  • Proficiency in Python and/or R, with experience using relevant bioinformatics frameworks
  • Experience developing and maintaining scalable data analysis pipelines and working with cloud-based infrastructure (e.g., AWS)
  • Excellent communication and presentation skills, with the ability to influence cross-functional stakeholders and translate complex data into clear, actionable insights
  • Demonstrated experience managing external CROs and bioinformatics vendors
  • Proven leadership experience, including mentoring and developing scientific teams
  • Strong cross-functional collaboration skills and ability to translate computational insights into biological and clinical impact
  • Ability to work both independently and collaboratively in a fast-paced environment, with strong organizational skills and attention to detail

Education/Background

  • PhD in Biological Sciences, Computational Biology, Biostatistics, Bioinformatics, Genomics, or a closely related discipline with 5+ years of industry experience.

The common requirements of an office environment (computers, computer screens, workstations, etc.) apply. This role is based in the South San Francisco office, with hybrid work arrangements possible.

Apply