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Single Cell Rna Sequencing Phd Jobs (NOW HIRING)

GC Therapeutics

Scientist - Epigenomics

Cambridge, MA · On-site

ATAC-seq, Cut&Run, Cut&Tag, single-cell RNA-seq). * Analyze and interpret next-generation sequencing datasets with support from the computational biology team. * Culture and maintain iPSC lines and ...

Washington University of St. Louis

... single-cell RNA sequencing, and epigenetics. We are seeking a highly motivated postdoctoral ... A recent PhD in Biochemistry, Cell or Molecular Biology with background in immunology. * Hands-on ...

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

As of Jun 30, 2026, the average hourly pay for single cell rna sequencing phd in the United States is $35.51, according to ZipRecruiter salary data. Most workers in this role earn between $29.09 and $40.38 per hour, depending on experience, location, and employer.

What is a Single Cell RNA Sequencing PhD?

A Single Cell RNA Sequencing PhD is a doctoral degree focused on the study and application of single-cell RNA sequencing (scRNA-seq) technologies. This field involves analyzing the gene expression profiles of individual cells, allowing researchers to understand cellular heterogeneity and complex biological processes at a granular level. PhD students in this area typically conduct original research, develop computational methods, and advance our understanding of cell biology, disease mechanisms, and potential therapeutic targets. Graduates often pursue careers in academia, biotechnology, or pharmaceutical research.

What is the difference between Single Cell Rna Sequencing Phd vs Single Cell Data Analyst?

AspectSingle Cell Rna Sequencing PhdSingle Cell Data Analyst
Required CredentialsPhD in Biology, Genetics, or related fieldBachelor's or Master's in Data Science, Biology, or related field
Work EnvironmentResearch labs, biotech companies, academic institutionsBiotech firms, research organizations, healthcare companies
Industry UsageDesigning experiments, interpreting sequencing data, publishing researchAnalyzing sequencing datasets, creating reports, data visualization

The Single Cell Rna Sequencing Phd typically involves designing experiments and interpreting complex sequencing data, requiring advanced research skills. In contrast, a Single Cell Data Analyst focuses on analyzing datasets, generating insights, and visualizing data, often with less emphasis on experimental design. Both roles are vital in the biotech industry but differ in their focus and required expertise.

What are some common challenges faced by researchers in a Single Cell RNA Sequencing PhD role, and how can they be addressed?

One of the main challenges in a Single Cell RNA Sequencing PhD role is managing and interpreting large, complex datasets generated from single-cell experiments. Researchers must be proficient in both wet-lab techniques and bioinformatics analysis, often requiring collaboration with computational biologists. Another challenge is ensuring sample quality and minimizing technical variability, which can significantly impact data reliability. Staying updated with rapidly evolving sequencing technologies and analytical tools is crucial, as is developing strong problem-solving skills to troubleshoot experimental or computational issues.

What are the key skills and qualifications needed to thrive as a Single Cell RNA Sequencing PhD, and why are they important?

To thrive as a Single Cell RNA Sequencing PhD, you need a strong background in molecular biology, bioinformatics, and genomics, typically supported by a PhD in a relevant field. Proficiency with single-cell sequencing platforms (e.g., 10x Genomics), next-generation sequencing (NGS) technologies, and computational analysis tools like R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating within multidisciplinary teams. These skills and qualifications are vital for designing robust experiments, analyzing high-dimensional data, and translating findings into impactful biological insights.
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Single Cell Rna Sequencing Phd jobs near you
Infographic showing various Single Cell Rna Sequencing Phd job openings in the United States as of June 2026, with employment types broken down into 18% Locum Tenens, 18% Full Time, 55% Part Time, and 9% Temporary. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $73,866 per year, or $35.5 per hour.
Research Scientist

Research Scientist

University of Virginia

Charlottesville, VA • On-site

Full-time

Posted 5 days ago

University Of Virginia rating

7.8

Company rating: 7.8 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

197th of 544 rated colleges and universities

Job description

Position summary
The Laboratory of Proteoform Medicine in the Department of Molecular Physiology and Biological Physics and the UVA Comprehensive Cancer Center is seeking a research scientist to lead a functional genomics program at the intersection of genetic screening, molecular biology, and multi-omics. The successful candidate will be a strong, versatile experimentalist and analyst who can design and run genetic perturbation screens, drive molecular biology and cell-based work, and generate and interpret omics data, particularly long-read RNA sequencing and mass spectrometry-based proteomics, alongside single-cell sequencing. These efforts connect directly to the lab's proteogenomics platform and its goal of resolving and functionally interrogating protein isoforms and proteoforms. This role is suited to a scientist who is equally comfortable in the dry and wet lab domains, who wants substantial intellectual ownership over a program area, and who is excited to build technology at the boundary of functional genomics and proteoform biology.
For the scientific vision behind this role, see our recent review: Korchak et al., "Proteoform medicine: characterizing and targeting protein forms in human disease," Nature Reviews Genetics 27, 271-291 (2026). This program builds out the vision of the map-perturb-predict framework described there.
Key responsibilities
  • Design and execute pooled and arrayed CRISPR screens (Cas9, Cas13, CRISPRi/a as appropriate) including library design and cloning, lentiviral production, transduction, selection, and NGS readout.
  • Develop and optimize gene perturbation approaches (knockout, knockdown, CRISPRi/a, and RNA-targeting Cas13 where isoform-level resolution is needed) in mammalian cell systems, including cancer cell lines and iPSC-derived models where applicable.
  • Generate, process, and integrate multi-omics data - long-read RNA sequencing, mass spectrometry-based proteomics, and single-cell sequencing - and connect these readouts with screen and perturbation outputs through robust experimental and computational pipelines.
  • Contribute to and lead molecular cloning workflows: guide library construction, vector design, plasmid prep, and verification by NGS.
  • Partner with computational lab members on bioinformatic analysis (count matrices, hit calling, QC); independently perform first-pass analysis using established tools and scripting in Python and/or R.
  • Mentor graduate students, postdocs, and research staff on functional genomics methods; help establish and document lab SOPs.
  • Lead writing of methods, manuscripts, and contribute to grant applications (NIH, foundation); present at lab meetings, departmental seminars, and external conferences.
  • Coordinate with collaborators across UVA and external partners on shared screening efforts.

Required qualifications
  • Ph.D. in molecular biology, genetics, biochemistry, biomedical engineering, computational biology, or a related field, with 3+ years of postdoctoral or equivalent independent research experience for the senior level (adjust per UVA classification).
  • Demonstrated, hands-on experience with genetic screening in mammalian cells - designing and executing pooled and/or arrayed CRISPR screens, or comparable functional-genomics screens - ideally evidenced by a first- or co-first-author publication or preprint.
  • Strong, hands-on molecular biology and cloning skills: vector design, Gibson/Golden Gate assembly, library construction (including sgRNA libraries), and plasmid validation.
  • Expertise in mammalian cell culture, including lentiviral packaging, titration, transduction, and stable line generation.
  • Strong NGS skills: sample prep (amplicon, RNA-seq, scRNA-seq library prep), QC, and familiarity with Illumina platforms.
  • Experience generating and/or analyzing omics data - for example bulk or single-cell RNA-seq - together with the aptitude and interest to work fluently with long-read RNA sequencing and mass spectrometry-based proteomics data.
  • Solid bioinformatics ability - comfortable on an HPC, scripting in Python and/or R, running standard analysis pipelines (CRISPR screens, RNA-seq, and related omics workflows), and analyzing results independently rather than waiting on a bioinformatics collaborator.
  • Strong written and verbal scientific communication; record of published peer-reviewed work.
  • Ability to plan independently, manage parallel projects, and mentor more junior team members.

Preferred qualifications
  • Direct experience with Cas13 (Cas13d, RfxCas13d, Cas13bt, etc.), including guide design for RNA targeting, knockdown validation, and trans-cleavage considerations.
  • Hands-on experience with single-cell genomics and perturbation platforms (e.g., 10x Genomics scRNA-seq, Perturb-seq, CROP-seq, ECCITE-seq) - including sample prep, library construction, and downstream demultiplexing/analysis using established frameworks. Single-cell is the primary readout for our screens, so prior experience here will accelerate ramp-up significantly.
  • Familiarity with iPSC culture and differentiation, or with primary patient-derived models.
  • A strong plus: knowledge of alternative splicing and genetics, and a background or active interest in isoform biology, proteogenomics, or protein/proteoform-level biology - including any experience with mass spectrometry-based proteomics, long-read RNA sequencing (PacBio Iso-Seq/Kinnex, Oxford Nanopore), or top-down proteomics.
  • Experience with high-content imaging, flow cytometry-based screen readouts, or FACS sorting for screens.
  • Track record of mentorship, training, or formal teaching.
  • Experience contributing to grant applications, technical reports, or consortium-level deliverables.

This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding. Salary is commensurate with education and experience.
Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar, and allows the appointee to publish the results of his/her research or scholarship during the training period
This position will sponsor applicants for work visas who meet the qualifications.
Start date is available immediately; the start date is flexible
Salary Range: 75k-85k salary
To Apply:
Please apply through Careers at UVA , and search for R0084368.
Complete an application online with the following documents:
  • CV
  • Cover letter
  • Contact information for 3 references.

Upload all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, merge all documents into one PDF for submission. Applications that do not contain all required documents will not receive full consideration.
Internal applicants: Search and apply for jobs on the UVA Internal Careers website .
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

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About University of Virginia

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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

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Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

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