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Single Cell Rna Sequencing Jobs (NOW HIRING)

Merck & Co.

... single-cell RNA sequencing, to characterize immune cell interactions and-identify-biomarkers associated with treatment response.-The ideal candidate will have experience in • biomarker assay ...

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

As of Jun 10, 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, and why are they important?

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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Single Cell Rna Sequencing jobs near you
Scientist I, Single-Cell Genomics

Scientist I, Single-Cell Genomics

Allen Institute

Seattle, WA • On-site

$86K - $106K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Scientist I, Single-Cell Genomics
The goal of Allen Institute for Cell Science is to develop a comprehensive approach to measure, describe, and model cell states and their dynamic changes over time with the ultimate goal of uncovering the fundamental principles of multiscale, multicellular morphogenesis, including how groups of cells organize and achieve collective behaviors essential for life. Our approach encompasses multi-modal data collection including live 3D timelapse imaging, data analysis, theory, and predictions to understand cell states and cell state transitions in human induced pluripotent stem cell models. As a division within the Allen Institute, the Allen Institute for Cell Science uses a team-oriented approach, focusing on accelerating foundational research, developing standards and models, and cultivating new ideas to make a transformational impact on science.
The Allen Institute for Cell Science seeks a collaborative Scientist I to support computational analysis of single-cell RNA-seq datasets in projects focused on cell-state transitions during tissue morphogenesis in human iPSC-derived 3D culture systems. This role is well suited to a scientist with strong biological grounding, quantitative skills, and an interest in using data analysis to generate clear biological insight.
The Scientist I will primarily analyze single-cell RNA-seq datasets, develop reproducible workflows and visualizations, and collaborate closely with experimental and computational colleagues to support biological discovery in human iPSC-derived 3D culture systems.
We believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.
We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions. Please submit a resume and cover letter to be considered for this role.
Essential functions
  • Perform analysis of single-cell RNA-seq datasets to characterize cell states, state transitions, and biological heterogeneity in human iPSC-derived 3D culture systems
  • Develop reproducible analysis workflows, code, and visualizations using sound data-analysis practices
  • Build and maintain R Shiny applications and related outputs to support data exploration and internal scientific decision-making
  • Collaborate with experimental and computational colleagues to interpret biological findings from data and align analysis plans with project goals, sample design, and metadata needs
  • Support data organization, documentation, and version control to enable effective collaboration and reuse
  • Stay current with methods and literature in single-cell genomics
  • Communicate findings clearly through presentations, figures, documentation, and manuscript contributions

Required Education and Experience
  • PhD in cell biology, developmental biology, stem cell biology, computational biology, bioengineering, biophysics, or a related field, or equivalent combination of education and experience
  • Experience analyzing single-cell RNA-seq datasets
  • Proficiency in R and/or Python for biological data analysis
  • Experience developing reproducible analysis workflows and clear data visualizations

Preferred Education & Experience
  • Proficiency in Linux-based computing environments and version control tools such as Git
  • Ability to build interactive data-exploration applications, such as R Shiny apps
  • Background in developmental biology, stem cell biology, morphogenesis, or cell-state transitions
  • Experience working with iPSC-derived model systems or 3D cell culture systems
  • Understanding of wet-lab assay design considerations and practical limitations of single-cell or spatial experiments
  • Knowledge of spatial biology approaches, including spatial transcriptomics and/or multiplexed protein imaging
  • Ability to work effectively on interdisciplinary projects with experimental and computational collaborators
  • Strong organizational, written, and verbal communication skills
  • Publication record demonstrating contribution to single-cell or related biological data analysis

Physical Demands
  • Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with equipment.

Position Type/Expected Hours of Work
  • This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 700 Dexter Ave N., with the flexibility to work remotely on a limited basis

Annualized Salary Range
  • $86,150 - $106,650*

* Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.
Benefits
Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute's Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute's 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute's benefits offering are located at the following link to the Benefits Guide: https://alleninstitute.org/careers/benefits.
It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities

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