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Single Cell Rna Seq R Jobs (NOW HIRING)

HHMI

Bioinformatic Specialist - Lim Lab

Princeton, NJ · On-site

Analyze and integrate single-cell RNA-seq, scATAC-seq, and other single-cell or multi-omic datasets ... Strong programming skills in R and/or Python. * Experience analyzing large-scale genomic ...

Axle

Data Scientist II

Rockville, MD

... seq, single-cell RNA-seq (scRNA-seq), spatial transcriptomics, Digital Spatial Profiling (DSP ... Strong proficiency in Python and R for analysis, scripting, and visualization. Hands-on experience ...

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How much do single cell rna seq r jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for single cell rna seq r 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 is a single cell RNA Seq R analyst?

A Single Cell RNA Seq R analyst is a bioinformatics specialist who uses the R programming language to analyze and interpret single-cell RNA sequencing (scRNA-seq) data. These professionals help researchers understand gene expression at the individual cell level, which can reveal important insights into cellular diversity, development, and disease processes. Their work involves tasks such as data preprocessing, quality control, dimensionality reduction, clustering, and visualization, often using specialized R packages like Seurat or SingleCellExperiment. They play a crucial role in designing analyses, troubleshooting workflows, and communicating results to biological scientists.

What are the key skills and qualifications needed to thrive as a single cell RNA Seq R researcher?

To excel as a Single Cell RNA-Seq Researcher, you need a background in molecular biology, genomics, and bioinformatics, typically with an advanced degree in a life science field. Proficiency in single-cell sequencing technologies, data analysis tools like Seurat or Scanpy, and scripting languages such as R or Python is essential. Analytical thinking, attention to detail, and strong communication skills help in interpreting complex data and collaborating across multidisciplinary teams. These abilities are crucial for producing reliable results and advancing research in genomics and cellular biology.

What are some common challenges faced when analyzing single-cell RNA-seq data using R, and how can they be addressed?

A frequent challenge in single-cell RNA-seq analysis with R is handling large, complex datasets that require substantial computational resources and efficient data management. Additionally, integrating quality control, normalization, and downstream analyses (such as clustering or trajectory inference) can be intricate due to the variety of available packages and methods. To address these issues, it's important to familiarize yourself with widely used R packages like Seurat or SingleCellExperiment, leverage high-performance computing resources when possible, and follow best practices for reproducible workflows. Collaborating closely with bioinformaticians and biologists can also help ensure analytical approaches align with project goals.

What is the difference between Single Cell Rna Seq R and Bioinformatics Analyst?

AspectSingle Cell Rna Seq RBioinformatics Analyst
Required CredentialsBiology or Bioinformatics degree, R programming skillsBiology, Computer Science, or related degree, R/Python skills
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageGenomics, transcriptomics, single-cell analysisData analysis, genomics, bioinformatics pipelines

Single Cell Rna Seq R specialists focus on analyzing single-cell RNA sequencing data using R, often working in research labs or biotech companies. Bioinformatics Analysts also work with genomic data but typically handle broader datasets and analysis pipelines. While both roles require strong R skills and biological knowledge, Single Cell Rna Seq R roles are more specialized in single-cell transcriptomics, whereas Bioinformatics Analysts have a wider scope in data analysis across various genomics projects.

What other helpful pages are available for Single Cell Rna Seq R?

Other pages related to Single Cell Rna Seq R:

Infographic showing various Single Cell Rna Seq R job openings in the United States as of September 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 78% Full Time, 15% Part Time, 4% Contract, and 1% Nights. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $45,021 per year, or $21.6 per hour.

Postdoctoral Research Associate, Cellular and Molecular Medicine

Tucson, AZ • On-site

University of Arizona
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of Arizonaexternal

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 21 days ago

University Of Arizona rating

7.4

Company rating: 7.4 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

Job description

Postdoctoral Research Associate, Cellular and Molecular Medicine
Posting Number
req27032
Department
Cellular & Molecular Medicine
Department Website Link
https://cmm.arizona.edu/
Location
Tucson Campus
Address
1501 N. Campbell Ave., Tucson, AZ 85719 USA
Position Highlights
The Romanoski Laboratory at the University of Arizona invites applications for a Postdoctoral Research Associate in vascular genomics and systems genetics. Our research program uses integrative genomics approaches to define the molecular mechanisms by which genetic variation shapes endothelial cell biology and confers risk for coronary artery disease (CAD) and microvascular dysfunction. The successful candidate will join a collaborative, scientifically rigorous environment at the intersection of vascular cell biology, chromatin biology, and human genetics.
This position offers hands-on training in state-of-the-art experimental and computational methods, including single-cell genomics, chromatin profiling, quantitative trait locus (QTL) mapping, and integration with large-scale biobank resources. The postdoc will contribute to active NIH-funded projects focused on shear stress-responsive RNAs and endothelial genetic mediators of microvascular dysfunction, with opportunities to develop independent research directions.
  • Visa sponsorship is not available for this position.
Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more!
The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocation services, please click here.
Duties & Responsibilities
The laboratory combines human endothelial cell culture andperturbation systems with genomic discovery tools to dissect how geneticvariation at CAD-associated loci operates through the vessel wall.
Activeresearch areas include:
  • Quantitative Trait Locus (QTL) mapping in human endothelial cell cohorts exposed to various in vitro environments.
  • Genetic and heterogeneity-based analysis of endothelial cell molecular traits using single-cell RNA sequencing and chromatin accessibility profiling .
  • Colocalization and Mendelian Randomization between genetic signals in endothelial cells and GWAS signals for vascular phenotypes.
  • Integration with population-scale biobanks including UK Biobank, All of Us, and others.
  • Functional characterization of candidate effector genes using laboratory assays for endothelial functions.

Primary Job Duties Include:
  • Design and execute experiments using primary human endothelial cells.
  • Prepare and QC sequencing libraries including bulk RNA-seq, small RNA-seq, ATAC-seq, and single-cell libraries.
  • Perform genome-scale mapping and genetic colocalization with GWAS summary statistics.
  • Analyze *-seq datasets using standard and custom bioinformatics pipelines.
  • Contribute to grant writing, manuscript preparation, and presentations at national conferences.
  • Mentor and support trainees and other members of the laboratory.

Knowledge, Skills & Abilities:
  • Ability operating specialized equipment in a laboratory setting.
  • Proficiency in sequencing library preparation, including bulk RNA-seq, small RNA-seq, ATAC-seq, and single-cell sequencing protocols.
  • Knowledge of genetic colocalization methods using GWAS and molecular QTL summary statistics.
  • Workingknowledge of large-scale biobank resources, particularly the All of US ResearchProgram and phenome-wide association study (PheWAS) frameworks.
  • Biologicalknowledge of vascular cell types, endothelial function, and the pathobiology ofatherosclerosis.

Minimum Qualifications
  • Doctoral degree (Ph.D.) in human genetics, genomics, molecular biology, cell biology, or a closely related field, conferred prior to the start date.
  • At least one first-author publication in a peer-reviewed journal in genetics, genomics, or vascular/cell biology.
  • Demonstrated experience with next-generation sequencing data analysis, including RNA-seq or single-cell RNA-seq.
  • Proficiency in at least one scripting or programming language used in genomics (R, Python, or Bash/Unix).
  • Experience with primary mammalian cell culturein a BSL-2 laboratory setting.

Preferred Qualifications
  • The ideal candidate will have a combination of experimental and computational expertise that spans the full arc from bench to genome-scale analysis.
The following qualifications are strongly preferred:
  • Experience culturing primary human endothelial cells.
  • Experience with CRISPR-based functional assays or other molecular perturbation approaches in human cell lines.
  • Single-cell genomics analysis experience.
  • VCF management, genotype processing, and whole-genome sequencing data handling.
  • Experience with QTL mapping and interpretation of results.
  • Strong publication record in genetics or vascular biology, with contributions to high-impact journals.
  • Experience presenting original research at national scientific conferences.
  • History of mentoring junior researchers (undergraduate or graduate students) in laboratory or computational settings.

FLSA
Exempt
Full Time/Part Time
Full Time
Number of Hours Worked per Week
40
Job FTE
1
Work Calendar
Fiscal
Job Category
Research
Benefits Eligible
Yes - Full Benefits
Rate of Pay
NIH salary guidelines, Depends on Experience
Compensation Type
salary at 1.0 full-time equivalency (FTE)
Type of criminal background check required:
Name-based criminal background check (non-security sensitive)
Number of Vacancies
1
Target Hire Date
Expected End Date
Contact Information for Candidates
Dr Casey Romanoski,cromanoski@arizona.edu
Open Date
9/11/2026
Open Until Filled
Yes
Documents Needed to Apply
Curriculum Vitae (CV), Cover Letter, and One Additional Document
Special Instructions to Applicant
Documents needed to apply:
  • A cover letter describing your research background, relevant experience, and motivation for joining the laboratory. (2 pages maximum)
  • A current curriculum vitae including a full publication list.
  • Contact information for three professional references.

Notice of Availability of the Annual Security and Fire Safety Report
In compliance with the Jeanne Clery Campus Safety Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University's campuses.Thesereports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures.
Paper copies of the Reports can be obtained by contacting the University Compliance Office at cleryact@arizona.edu.

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