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Spatial Transcriptomics Jobs in California (NOW HIRING)

Mithrl

Bioinformatics Engineer, Pipelines

San Francisco, CA · On-site

$150K - $200K/yr

These workflows include microarray, imaging, spatial transcriptomics, genomics, epigenomics, flow cytometry, and more. This role sits at the center of our technical stack. You will architect Nextflow ...

Mithrl

Bioinformatics Engineer, Pipelines

San Francisco, CA · On-site

$150K - $200K/yr

These workflows include microarray, imaging, spatial transcriptomics, genomics, epigenomics, flow cytometry, and more. This role sits at the center of our technical stack. You will architect Nextflow ...

Transcripta Bio

Computational Biologist

Palo Alto, CA · On-site

Familiarity with spatial transcriptomics or multimodal data integration approaches. * Experience working with or alongside ML/AI teams; familiarity with applying machine learning methods to ...

Caltech

Research Scientist

Pasadena, CA · On-site

... cell and spatial transcriptomics, multiomics and related technologies. The successful applicant will: 1) play a key role in developing and rigorously testing new methods in the above areas; 2) ...

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 ...

City of Hope

Postdoctoral Fellow - Genomics Research

Duarte, CA · On-site

$51.40K - $69.80K/yr

Perform collaborative research with multiple faculty members at ARDMRI on projects involving genomics data analysis using single cell RNA-seq, CHIP-seq/ATAC-seq, spatial transcriptomics, HiC/HiCHIP ...

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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Spatial Transcriptomics information

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

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 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 popular job titles related to Spatial Transcriptomics jobs in California? For Spatial Transcriptomics jobs in California, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics jobs in California look for? The top searched job categories for Spatial Transcriptomics jobs in California are:
What cities in California are hiring for Spatial Transcriptomics jobs? Cities in California with the most Spatial Transcriptomics job openings:
Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in California as of May 2026, with employment types broken down into 3% Internship, 78% Full Time, 5% Part Time, 3% Temporary, 8% Contract, and 3% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.
Senior Bioinformatics Scientist

Senior Bioinformatics Scientist

AA2IT

South San Francisco, CA • On-site

$75 - $85/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Title: Bioinformatics Scientist - III Location: 3050 Science Park Road, San Diego, CA Rate: $75-85/HR Education: • Minimum qualification: Master's degree with 4+ years of experience in computational biology, bioinformatics or related fields. • Advance degree- PhD in computational biology, bioinformatics, or related fields. Required experience and skills: • Experience in biotech or pharmaceutical industries is a plus.

• Advanced skills in a high-level programming language such as R or Python for data analysis and visualization. • Expertise in downstream analysis for common NGS data types, such as WGS/WES/panel-seq, bulk RNA-seq, single-cell RNAseq and spatial transcriptomics (experience in building NGS pipelines is not required but is a plus). • Basic understanding of disease biology and molecular/cellular mechanisms in immunology.

• Expertise in network and systems biology is required. • Expertise in contemporary machine-learning/AI methods is a plus. Personality: Are you a computational biologist with a passion for unraveling the complexities of the immune system?

• If you have a strong foundation in bioinformatics, 'omics analysis, network biology, and systems biology, along with a deep understanding of molecular and cellular immunology, we'd love to hear from you. • Your work will be instrumental in driving precision medicine and drug development by dissecting the molecular mechanisms underlying immune-mediated diseases. • We welcome applications from individuals with a track record of innovative translational research in immunology, regardless of their current setting (clinical, academic, or industrial).

Note: • 100% onsite role. • Remote working candidates will not be considered. • Positions available: 2 Responsibilities: We are looking for a contractor with extensive experience in computational biology and join our immunology analytics team in Translational Genome Analytics, San Diego.

• Use computational methods to identify molecular subtypes with unmet need in immune mediated diseases. • Conduct in-depth analyses to uncover the key biological functions and disease mechanisms driving disease subtypes. • Collaborate with multi-disciplinary teams to pinpoint potential therapeutic targets.

• Contribute to accurately represent key disease states in model systems and other validation scenarios. • Work closely with discovery immunology teams in the iterative process of validation of therapeutic candidates and/or mechanistic hypotheses. • Summarize your findings and report conclusions to Client stakeholders.

MUST HAVE: • Working closely with collaborator in San Diego. • Quick discussion onsite in real time. • Work environment is face to face, so need person onsite.

• Collaborating with different groups onsite is must. Interested candidate to share your resume and answers to below question: Q1: How many years of exp in computational biology, bioinformatics or related fields. Q2: How many years of exp in biotech or pharmaceutical industries Q3: How many years of exp in downstream analysis for common NGS data types, such as WGS/WES/panel-seq, bulk RNA-seq, single-cell RNAseq and spatial transcriptomics (experience in building NGS pipelines is not required but is a plus).

Q4: How many years of exp in network and systems biology Q5: How far you live from 3050 Science Park Road, San Diego, CA and how will you commute daily

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