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Atlas Genomics Jobs in California (NOW HIRING)

Transcripta Bio

Computational Biologist

Palo Alto, CA · On-site

Contribute to the curation and expansion of the Drug-Gene Atlas: ensure that data inputs are well ... PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of ...

Transcripta Bio

Scientist, Drug Discovery

Palo Alto, CA · On-site

$120 - $180/hr

... Atlas, Drug-Gene Atlas, and Conductor AI platform -- that integrates single-cell patient ... Preferred * Experience with functional genomics approaches. * Familiarity with transcriptomics ...

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Atlas Genomics information

See California salary details

$27.4K

$87.8K

$172.8K

How much do atlas genomics jobs pay per year?

As of Aug 24, 2026, the average yearly pay for atlas genomics in California is $87,785.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,554.00 and $124,362.00 per year, depending on experience, location, and employer.

What is Atlas Genomics?

Atlas Genomics is a clinical laboratory company specializing in advanced genomic testing and molecular diagnostics. They provide healthcare providers with innovative testing services, such as genetic screening, infectious disease diagnostics, and personalized medicine solutions. Their laboratory uses state-of-the-art technology to deliver fast, accurate results that help guide patient care and treatment decisions. Atlas Genomics also partners with medical professionals to ensure that testing is clinically relevant and easy to integrate into practice.

What are the typical responsibilities of a laboratory technologist at Atlas Genomics, and how do they collaborate with other teams?

At Atlas Genomics, laboratory technologists are primarily responsible for processing and analyzing genetic samples using advanced molecular techniques such as PCR and next-generation sequencing. They work closely with the quality assurance team to ensure data accuracy and compliance with regulatory standards. Collaboration with bioinformatics specialists and clinical coordinators is frequent, as technologists provide crucial data that informs diagnostic reports and research initiatives. The lab environment is fast-paced, requiring strong communication skills and the ability to adapt to evolving technologies and protocols.

What are the key skills and qualifications needed to thrive as a genomics laboratory technician, and why are they important?

To thrive as a Genomics Laboratory Technician, you need a solid background in molecular biology, genetics, and laboratory techniques, typically supported by a degree in a life science field. Familiarity with next-generation sequencing (NGS) platforms, laboratory information management systems (LIMS), and relevant certifications such as ASCP can be highly beneficial. Attention to detail, strong problem-solving abilities, and effective teamwork are crucial soft skills for this role. These competencies ensure accuracy, efficiency, and reliability in processing and analyzing complex genomic data, which is vital for high-quality laboratory results.

What is the difference between Atlas Genomics vs Genetic Technician?

AspectAtlas GenomicsGenetic Technician
Required CredentialsTypically requires a bachelor's degree in genetics, biology, or related fieldUsually requires an associate degree or bachelor's in genetics or biology
Work EnvironmentLaboratories, research facilities, healthcare settingsLaboratories, hospitals, research institutions
Industry UsageResearch, diagnostics, biotech companiesClinical labs, research, healthcare providers

Atlas Genomics and Genetic Technicians both work in genetics-related fields, often in laboratory settings. While Atlas Genomics may focus more on research and advanced genetic analysis, Genetic Technicians typically perform routine testing and sample processing. Both roles require relevant education and are integral to genetic research and diagnostics, but Atlas Genomics often involves more specialized tasks and higher-level responsibilities.

What are popular job titles related to Atlas Genomics jobs in California?

For Atlas Genomics jobs in California, the most frequently searched job titles are:

What job categories do people searching Atlas Genomics jobs in California look for?

The top searched job categories for Atlas Genomics jobs in California are:

Atlas Genomics jobs near you
Infographic showing various Atlas Genomics job openings in California as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $87,785 per year, or $42.2 per hour.

Computational Biologist

Palo Alto, CA • On-site

Transcripta Bio
See more jobs at Transcripta Bioexternal

Full-time

Re-posted yesterday

Job description

About Transcripta Bio
Transcripta Bio is a preclinical-stage AI drug discovery company pioneering a patient-first approach to therapeutics. Headquartered in Palo Alto, CA, we have built a proprietary closed-loop discovery engine - comprising our Disease Signature Atlas, Drug-Gene Atlas, and Conductor AI platform - that integrates single-cell patient transcriptomics, causal human genetics, and pre-validated chemistry to identify and advance drug candidates with a structural edge over conventional approaches.
WHAT YOU'LL DO
  • Develop, maintain, and optimize reproducible bioinformatics pipelines for processing, QC, and analysis of high-throughput datasets, including bulk RNA-seq, single-cell RNA-seq, and high-content imaging data.
  • Analyze data from drug perturbation screens to identify transcriptomic signatures, compound-gene associations, and patterns of drug response across disease-relevant cell models.
  • Integrate data across multiple experimental modalities (transcriptomics, imaging, protein measurements) to build a coherent picture of biology and prioritize therapeutic hypotheses.
  • Partner with wet lab scientists to help design experiments, define data standards, troubleshoot data quality issues, and ensure clean handoffs between experimental and computational workflows.
  • Contribute to the curation and expansion of the Drug-Gene Atlas: ensure that data inputs are well characterized, analysis methods are calibrated, and outputs are interpretable and reliable.
  • Communicate findings clearly through reports, visualizations, and presentations to both computational and non-computational colleagues.
  • Stay current with advances in transcriptomics, single-cell methods, and computational biology; evaluate and adopt new tools and approaches where they add value.
  • Contribute to code review, documentation, and best practices as the team grows.

WHAT YOU'LL BRING
  • PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of relevant experience in industry.
  • Extensive hands-on experience processing and analyzing bulk and/or single-cell RNA-seq data, from raw reads through QC, normalization, dimensionality reduction, clustering, and differential expression.
  • Experience in relevant scientific packages (e.g., scanpy, pandas, numpy, DESeq2, ggplot2) and comfort working in a Linux/command-line environment. Strong programming proficiency in Python and/or R is a plus
  • Experience building and running reproducible workflows using tools such as Snakemake, Nextflow, or equivalent; familiarity with version control (Git) and best practices for collaborative code development.
  • Exposure to high-throughput or perturbational screening datasets (chemical, genetic, or combined) is highly desirable.
  • A biologically grounded mindset: you approach data with mechanistic questions in mind, not just statistical outputs.

NICE TO HAVE
  • Experience analyzing data from functional genomics assays (e.g., ATAC-seq, ChIP-seq, perturb-seq, or pooled CRISPR screens).
  • Familiarity with spatial transcriptomics or multimodal data integration approaches.
  • Experience working with or alongside ML/AI teams; familiarity with applying machine learning methods to biological data.
  • Background in rare genetic disease, neurodegeneration, or other genetically defined disease areas.
  • Experience in cloud-based compute environments (AWS, GCP, or equivalent)

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