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Single Cell Rna Sequencing Jobs (NOW HIRING)

Sr. Biological Scientist

Tampa, FL ยท On-site

$83K - $114K/yr

Perform Next-Generation Sequencing (NGS) sample preparation and sequencing, including single-cell RNA-seq (scRNA-seq, snRNA-seq) and spatial transcriptomics (Visium HD) workflows, DNA/RNA library ...

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in immunology, cell biology, and genomics, with experience developing highly robust and reproducible assays ...

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in immunology, cell biology, and genomics, with experience developing highly robust and reproducible assays ...

... sequencing and single-cell RNA-seq. The ideal candidate has a strong technical background in immunology, cell biology, and genomics, with experience developing highly robust and reproducible assays ...

$78K - $117K/yr

Establish and optimize RNA sequencing protocols for single-cell or spatial transcriptomics applications;Understand and anticipate broader project/team interests, identifying, proposing, and ...

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How much do single cell rna sequencing jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for single cell rna sequencing in the United States is $21.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What are some common challenges faced by researchers working in single cell RNA sequencing, and how can they be addressed?

Researchers in Single Cell RNA Sequencing often encounter challenges such as sample preparation variability, data complexity, and managing large datasets. Ensuring high-quality single-cell suspensions and minimizing cell loss during processing are critical steps. Additionally, interpreting data requires proficiency with bioinformatics tools and collaboration with computational biologists. Staying up-to-date with evolving protocols and leveraging multi-disciplinary teamwork can help address these challenges effectively.

What is the difference between Single Cell Rna Sequencing vs Single Cell Genomics Technician?

AspectSingle Cell Rna SequencingSingle Cell Genomics Technician
CredentialsTypically requires a degree in biology, molecular biology, or related fields; experience with sequencing technologiesSimilar credentials; often with laboratory or technical certifications in genomics
Work EnvironmentLaboratories performing sequencing, data analysis, and sample preparationLaboratories focused on sample processing, sequencing support, and data collection
Industry UsageUsed in research labs, biotech, and pharmaceutical companies for gene expression studiesCommon in genomics research centers, biotech firms, and academic labs

Both roles involve working with genomic technologies and require similar educational backgrounds. However, Single Cell Rna Sequencing specialists focus more on RNA analysis and data interpretation, while Single Cell Genomics Technicians support sample preparation and sequencing workflows. Understanding these differences helps in choosing the right career path or job search focus.

What are the key skills and qualifications needed to thrive as a single cell RNA sequencing specialist?

To thrive as a Single Cell RNA Sequencing Specialist, you need a solid background in molecular biology, genomics, and data analysis, typically supported by a relevant degree in the life sciences. Familiarity with sequencing platforms (such as 10x Genomics or Illumina), bioinformatics tools (like Seurat or Cell Ranger), and experience with data visualization are crucial. Attention to detail, problem-solving ability, and strong communication skills help ensure accurate results and effective collaboration with research teams. Mastering these skills is essential for generating high-quality data, troubleshooting experiments, and translating complex findings into actionable insights.

What is single cell RNA sequencing?

Single cell RNA sequencing (scRNA-seq) is a technique that allows researchers to examine the gene expression profiles of individual cells. Unlike traditional RNA sequencing, which measures average gene expression across thousands or millions of cells, scRNA-seq reveals the unique transcriptomic signature of each cell. This method is valuable for studying cellular diversity, identifying rare cell types, and understanding complex biological processes such as development, disease progression, and immune responses.
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Infographic showing various Single Cell Rna Sequencing job openings in the United States as of August 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 97% In-person, and 3% Remote job distribution, with an average salary of $45,021 per year, or $21.6 per hour.

Computational Scientist (Functional Genomics) - Remote

Astrix Inc

South San Francisco, CA โ€ข On-site, Remote

$35 - $40/hr

Full-time, Contractor

Posted 21 days ago


Job description

Pay Rate Low: 35 | Pay Rate High: 40
Our client is an innovative biotechnology company seeking a Computational Scientist to support advanced research initiatives focused on analyzing large-scale single-cell perturbation datasets.
Title: Computational Scientist - Single-Cell Genomics & Perturbation Biology
Location: Remote (Must be open to working PST)
Schedule: Full-Time (40 hours/week)
Duration: 12-Month Contract (+Benefits)
Pay rate: $35-40/hr
In this role, you will leverage computational approaches to generate biological insights that accelerate target identification, drug discovery, and the development of next-generation therapeutics. This role will partner with cross-functional teams of computational scientists, biologists, and data scientists to generate biological insights from high-content sequencing data while contributing to scalable computational pipelines and best practices.
Key Responsibilities
  • Analyze large-scale perturbation sequencing datasets (e.g., Perturb-seq, CROP-seq, multi-condition single-cell RNA-seq).
  • Develop and apply computational methods to generate insights that support early-stage therapeutic research.
  • Collaborate with interdisciplinary teams across computational biology, biology, chemistry, and data science.
  • Contribute to software, analysis pipelines, and workflow improvements for large-scale genomic data analysis.
  • Present findings and communicate complex analyses to technical and non-technical stakeholders.

Qualifications
  • Master's or PhD in Bioinformatics, Computational Biology, Computer Science, Statistics, Mathematics, or a related quantitative life science field.
  • 1-3+ years of relevant industry or postdoctoral experience.
  • Hands-on experience analyzing Perturb-seq, CROP-seq, SciPlex, or other multi-condition single-cell RNA-seq datasets.
  • Strong programming skills in Python and/or R.
  • Experience working in HPC environments (SLURM, AWS, SGE, or similar).
  • Must be authorized to work in the United States without sponsorship.
  • Knowledge of workflow management tools such as Nextflow or Snakemake is preferred.
  • Strong software engineering fundamentals and experience with version control.
  • Excellent analytical, problem-solving, and communication skills.

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