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Transcriptomics Jobs in California (NOW HIRING)

Integrate data across multiple experimental modalities (transcriptomics, imaging, protein measurements) to build a coherent picture of biology and prioritize therapeutic hypotheses. * Partner with ...

Computational Biologist

San Francisco, CA · On-site

$125K - $185K/yr

This coming year, we're on track to scale our patient volume significantly, all while bringing new diagnostic modalities (e.g., single-cell transcriptomics) and analytical approaches into clinical ...

In this role, you will drive the use of high-throughput, transcriptomics, epigenomics, proteomics, and functional genomics data to identify and prioritize novel therapeutic targets. You will bring a ...

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Transcriptomics information

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

To thrive as a Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a relevant field. Familiarity with next-generation sequencing (NGS) platforms, RNA-seq analysis pipelines, and programming languages like R or Python is essential. Attention to detail, problem-solving abilities, and effective communication skills set outstanding candidates apart. These competencies are vital for generating accurate transcriptomic data, interpreting complex results, and collaborating within multidisciplinary research teams.

What does transcriptomics do?

Transcriptomics is a field within molecular biology that studies the complete set of RNA transcripts produced by a genome under specific conditions. Professionals in this area analyze gene expression patterns using tools like RNA sequencing to understand cellular functions and disease mechanisms.

What biology jobs pay over $100k?

In the field of transcriptomics, roles such as senior research scientist, bioinformatics director, and molecular biology manager often have salaries exceeding $100,000 annually. These positions typically require advanced degrees, extensive experience, and skills in data analysis, programming, and laboratory techniques.

What is transcriptomics?

Transcriptomics is the study of the complete set of RNA transcripts produced by the genome under specific circumstances or in a specific cell. It provides insights into gene expression patterns, how genes are regulated, and how cells respond to various conditions. By analyzing the transcriptome, researchers can better understand biological processes, disease mechanisms, and identify potential targets for therapy. Technologies such as RNA sequencing (RNA-seq) are commonly used in transcriptomics research.

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

Professionals in transcriptomics frequently encounter challenges such as handling large and complex datasets, ensuring data quality, and staying current with rapidly evolving analytical tools and technologies. Working closely with bioinformaticians and statisticians is essential for effective data analysis and interpretation. Additionally, clear communication and collaboration with wet-lab biologists and clinicians help bridge the gap between raw data and meaningful biological insights. Regular training and professional development can help transcriptomics professionals stay updated with the latest best practices and software advancements.

What is the highest paying job in genetics?

In genetics, roles such as genetic counselors, research directors, and senior clinical geneticists tend to have the highest salaries, often exceeding six figures annually. Positions requiring advanced degrees, specialized skills, and leadership responsibilities typically offer the highest compensation in the field.

What is the highest paying job in bioinformatics?

In bioinformatics, senior roles such as bioinformatics directors, principal scientists, or lead data scientists tend to have the highest salaries, often exceeding $150,000 annually. These positions typically require advanced skills in programming, data analysis, and experience with large-scale genomic or transcriptomic data, along with leadership responsibilities.

What is the difference between Transcriptomics vs Bioinformatics?

AspectTranscriptomicsBioinformatics
Required credentialsBachelor's or Master's in Biology, Genetics, or related fields; experience with sequencing technologiesBachelor's or Master's in Computer Science, Bioinformatics, or related fields; programming skills
Work environmentLaboratories, research institutions, biotech companiesResearch labs, biotech firms, academic institutions, data analysis centers
Industry usageGenomics, molecular biology, medical researchData analysis, software development, computational biology

While both Transcriptomics and Bioinformatics involve analyzing biological data, Transcriptomics focuses on studying gene expression profiles using sequencing technologies, whereas Bioinformatics encompasses a broader range of computational methods to analyze various biological datasets. Professionals in both fields often collaborate but have distinct skill sets and work environments.

What job categories do people searching Transcriptomics jobs in California look for? The top searched job categories for Transcriptomics jobs in California are:
What cities in California are hiring for Transcriptomics jobs? Cities in California with the most Transcriptomics job openings:
Infographic showing various Transcriptomics job openings in California as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, 1% Temporary, and 2% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.
Scientist II, Clinical Bioinformatics

Scientist II, Clinical Bioinformatics

10x Genomics

Pleasanton, CA • On-site

Other

Posted 18 days ago


Job description

About The Role

10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Scientist II to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights.

The role requires a biology-first mindset, proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor. The successful candidate will have an opportunity to work with some of the largest biomedical datasets assayed using cutting-edge 10x Genomics technologies, deriving clinical insights that power the next generation of clinical diagnostics.

What You Will Be Doing:

  • Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis.
  • Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets.
  • Design, implement and validate biomarkers for diagnostic applications.
  • Implement and maintain bioinformatics pipelines for reproducible, large-scale data processing.
  • Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.

To Be Successful, You Will Need:

  • Ph.D. in bioinformatics, computational biology, genomics or a related discipline with extensive hands-on experience in single-cell NGS data analysis.
  • A minimum of 2 years of industry experience post Ph.D.
  • Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers.
  • In-depth understanding of the assumptions, limitations and caveats of statistical methods.
  • Experience developing and optimizing high-performance, scalable code.
  • Proficiency working in a Linux environment.
  • Goal-oriented, self-motivated and an independent problem solver.
  • Meticulous attention to detail and a conscientious work ethic.

Preferred Skills

  • Hands-on experience with 10x Genomics single-cell and in-situ transcriptomics technologies is a strong preference
  • Hands-on research experience in cancer or autoimmune diseases is a strong preference
  • Knowledge of clinical genomics, biomarker discovery and diagnostics
  • Development of statistical models and algorithms for single-cell or spatial transcriptomics data
  • Application of machine learning, particularly in the context of genomics
  • Proficiency with workflow orchestration frameworks such as Snakemake, Nextflow or Martian
  • Programming best practices including data analysis reproducibility, version control, design patterns, testing, debugging and profiling
  • Track record of writing production-level code or maintaining published software packages
  • High-throughput computing infrastructure such as HPCs or cloud computing