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Spatial Transcriptomics Jobs in San Diego, CA (NOW HIRING)

Novartis

Director Pathology

San Diego, CA · Hybrid

$204K - $379K/yr

Ability to synthesize complex molecular datasets (RNA-seq, proteomics, spatial transcriptomics) in the context of tissue biology and pathology. Strong cross-functional influence and comfort operating ...

Novartis Group Companies

Director Pathology

San Diego, CA · On-site

$204K - $379K/yr

Ability to synthesize complex molecular datasets (RNA-seq, proteomics, spatial transcriptomics) in the context of tissue biology and pathology. * Strong cross-functional influence and comfort ...

Novartis

Director Pathology

San Diego, CA · On-site

$204K - $379K/yr

... spatial transcriptomics) in the context of tissue biology and pathology. • Strong cross-functional influence and comfort operating in governance forums and matrixed teams. • Commitment to ...

Acelabio, Inc

Business Development Director

San Diego, CA · On-site

$86K - $143K/yr

We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics, and biomarker endpoints to pharmaceutical and biotechnology sponsors. Our team is scientifically ...

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All JobsSpatial Transcriptomics JobsSpatial Transcriptomics Jobs in San Diego, CA

Spatial Transcriptomics information

See San Diego, CA salary details

$52K

$216K

$424.7K

How much do spatial transcriptomics jobs pay per year?

As of Aug 7, 2026, the average yearly pay for spatial transcriptomics in San Diego, CA is $216,024.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,300.00 and $424,700.00 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 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 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 popular job titles related to Spatial Transcriptomics jobs in San Diego, CA? For Spatial Transcriptomics jobs in San Diego, CA, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics jobs in San Diego, CA look for? The top searched job categories for Spatial Transcriptomics jobs in San Diego, CA are:
What cities near San Diego, CA are hiring for Spatial Transcriptomics jobs? Cities near San Diego, CA with the most Spatial Transcriptomics job openings:
Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in San Diego, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, 17% Hybrid, and 33% Remote job distribution, with an average salary of $216,024 per year, or $103.9 per hour.

Senior Scientist, Bioinformatics

Kenai Therapeutics

San Diego, CA • On-site

$140K - $155K/yr

Full-time

Re-posted 6 days ago

Job description

Kenai Therapeutics is seeking a skilled and versatile computational biologist to join our highly collaborative, multidisciplinary, and dynamic team advancing next-generation allogeneic cell therapies for neurological diseases. As Senior Scientist of Bioinformatics, the ideal candidate will drive computational analysis and pipeline development across CMC and research programs. This candidate brings scientific rigor, deep hands-on expertise in single-cell and multiomics analysis, and a strong foundation in statistics and machine learning to generate actionable insights that inform therapeutic decision-making. This role requires exceptional technical skills, a proven ability to communicate complex findings across scientific disciplines, and a desire to thrive in a small, fast-moving organization where flexibility and initiative are essential.
Key Responsibilities:
  • Design, implement, and maintain scalable, reproducible pipelines for single-cell RNA-seq, spatial transcriptomics, and integrative multiomics data analysis, from raw data through biological interpretation
  • Apply statistical modeling and machine learning approaches to large-scale omics datasets to identify biomarkers, characterize cellular heterogeneity, and aid process development
  • Leverage AI-based tools and platforms to accelerate research workflows, automate analyses, and enhance software development productivity
  • Perform complex data interpretation across modalities (scRNA-seq, genomics, spatial omics, proteomics) and translate findings into actionable insights for programs and leadership
  • Partner closely with manufacturing and research teams to align computational efforts with therapeutic objectives and program priorities
  • Contribute to data infrastructure strategy, supporting robust systems for data storage, integration, traceability, and long-term analytics
  • Communicate results effectively through internal presentations, and cross-functional meetings; distill complex analyses into clear narratives for diverse audiences.

Requirements
  • Ph.D. in bioinformatics, computational biology, genomics, statistics, or a related quantitative discipline with 3+ years of relevant industry experience
  • Self-motivated, hardworking, and adaptable
  • Strong foundation in statistics and machine learning, including supervised and unsupervised methods, dimensionality reduction, and model evaluation
  • Deep hands-on experience with single-cell analysis frameworks (e.g., Scanpy, Seurat, scVI) and associated workflows across the full analytical lifecycle
  • Strong proficiency in Python and R for data analysis, visualization, and pipeline development; Javascript experience is a plus
  • Demonstrated experience supporting drug discovery and development programs with computational and bioinformatic analyses
  • Proficiency in utilizing AI and large language model-based tools for research acceleration and software development
  • Excellent written and verbal communication skills, including the ability to present complex technical work to both computational and non-computational audiences
  • Strong team player with a collaborative mindset and a commitment to working in a small, tight-knit, and high-performing team environment

Preferred
  • Background in neuroscience, developmental biology, or related areas of disease biology
  • Experience in cell therapy research, manufacturing analytics, or related cell-based therapeutic modalities
  • Familiarity with spatial transcriptomics platforms (e.g., 10x Visium, Xenium, MERFISH) and integrative multiomics approaches
  • Track record of scientific contributions evidenced by peer-reviewed publications, patents, or conference presentations

Benefits
Kenai Therapeutics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
The salary range for this position is $140,000 USD to $155,000 USD annually. This salary range is an estimate, and the actual salary may vary based on experience and/or the Company's compensation practices.

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