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Transcriptomics Jobs in San Pablo, CA (NOW HIRING)

Buck Institute

AI Data Scientist-Furman lab

Novato, CA · On-site

Transcriptomics, including single-cell and bulk RNA-seq * Proteomics * Metabolomics * Epigenetics and biological aging clocks * Clinical and phenotypic datasets * Survey data * Integrative multi ...

Valius Sciences

Head/VP of Engineering

San Francisco, CA · On-site

$250K - $350K/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 ...

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All JobsTranscriptomics JobsTranscriptomics Jobs in San Pablo, CA

Transcriptomics information

See San Pablo, CA salary details

$55.2K

$229.3K

$450.8K

How much do transcriptomics jobs pay per year?

As of Aug 30, 2026, the average yearly pay for transcriptomics in San Pablo, CA is $229,294.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $450,800.00 per year, depending on experience, location, and employer.

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 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 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 cities near San Pablo, CA are hiring for Transcriptomics jobs?

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

Transcriptomics jobs near you
Infographic showing various Transcriptomics job openings in San Pablo, CA as of June 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 94% Physical, 4% Hybrid, and 2% Remote job distribution, with an average salary of $229,294 per year, or $110.2 per hour.

Senior Director, Artificial Intelligence

Foster City, CA • On-site

Cellanome
Biotechnology Research and Development • 11 - 50 employees
Learn more about Cellanomeexternal

$288K - $330K/yr

Full-time

Re-posted 6 days ago

Job description

The Senior Director, Artificial Intelligence will lead our Artificial Intelligence (AI) and Machine Learning (ML) efforts. AI and ML are integral to multiple aspects of the operation of our platform and represent a key strategic area for Cellanome. This position will grow our existing efforts in these areas and identify future opportunities to leverage AI and ML to further our goals. This is a leadership position with the Computational Biology team and will collaborate closely with R&D, Software Engineering and Product Development through both Research and Product Development programs. This role will provide leadership and vision, while working hands-on in the implementation. 

Essential Duties include but are not limited to the following:

  • Design, develop, train and productize cutting-edge Deep Learning models, particularly in the area of image processing for tasks such as image segmentation, classification, unsupervised and semi-supervised feature extraction.
  • Research and develop models for integrating paired imaging and transcriptomic data from the same cells.
  • Design and develop infrastructure for tracking model learning and performance.
  • Develop and implement a multi-year strategy for application of ML and AI-based methodologies to core aspects of the operation of our technology, and interpretation of the resulting data.
  • Identify new opportunities to deploy ML and AI-based methodologies based on conversations with internal and external stakeholders.
  • Source, hire and mentor junior team members, fostering an environment of healthy teamwork and continuous learning.
  • Work collaboratively with other software teams to integrate ML and AI-based methodologies into our broader software ecosystem.
  • Keep up with the rapidly changing AI and ML landscape to identify new opportunities.
  • Ability to work in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel up to 5% of working time away from work location, may include overnight/weekend travel at times. 

Minimum Qualifications:

  • PhD in Engineering, computer science, computational biology or related fields with 15 years experience; or a Master's degree with 18 years experience; or a Bachelor's degree with 20 years experience; or equivalent experience. 
  • A minimum of 10 years of leadership experience, including hiring and mentoring junior team members. 
  • Comprehensive knowledge of Deep Learning-based methodologies for image analysis is a must. The successful candidate will have extensive familiarity with object detection, instance segmentation and feature extraction models and will have demonstrated experience training and tweaking them.  
  • Excellent programming skills and intimate familiarity with commonly used Deep Learning frameworks such as PyTorch, TensorFlow etc. 
  • Excellent problem-solving abilities, critical thinking, and communication skills.
  • Demonstrated ability to perform the Essential Duties of the position with or without reasonable accommodations.

Preferred Qualifications:

  • PhD strongly preferred.
  • Experience working with biological imaging data (e.g. live cell microscopy, histopathology).
  • Experience working with foundation models for single-cell transcriptomics.
    •  

The estimated base salary range for this position is $288,000- $330,000/year. Within the range, individual pay is determined by work location and additional factors including job related skills, experience, and relevant education or training.  

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