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Single Cell Rna Sequencing Phd Jobs in California

University of California San Francisco

SRA 1

San Francisco, CA · On-site

$41.50 - $52/hr

Experience in R Studio and/or Python to analyze single-cell RNA sequencing, bulk RNA sequencing, and whole-exome sequencing data * Experience in molecular biology techniques such as sgRNA cloning and ...

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Single Cell Rna Sequencing Phd information

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 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.

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 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.

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For Single Cell Rna Sequencing Phd jobs in California, the most frequently searched job titles are:

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Cities in California with the most Single Cell Rna Sequencing Phd job openings:

Single Cell Rna Sequencing Phd jobs near you
Infographic showing various Single Cell Rna Sequencing Phd job openings in California as of August 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 81% Full Time, 14% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Computational Scientist II - Single Cell Genomics

Dawar Consulting

South San Francisco, CA • On-site

$73.87 - $105.21/hr

Other

Medical, Dental, Vision, Retirement

Re-posted 14 days ago

Job description

Computational Scientist II - Single Cell Genomics

South San Francisco, United States | Posted on 07/08/2026

Our Client, a world leader in Biotechnology is looking for a Computational Scientist II for SSF, CA

Job Duration: Long Term Contract (Possibility Of Extension)

Pay Rate: $65/hr on W2

Company Benefits: Medical, Dental, Vision, Paid Sick leave, 401K

This role is focused on advancing therapeutic discovery through high-content perturbation screening and single-cell genomics. This role will involve analyzing large-scale sequencing datasets, developing computational pipelines, and collaborating with multidisciplinary teams to generate biological insights that support drug discovery.

Key Responsibilities
  • Analyze and interpret large-scale single-cell sequencing datasets (scRNA-seq) generated from high-content perturbation experiments.
  • Develop and optimize computational workflows for Perturb-seq, CROP-seq, Sci-Plex, and other sequencing-based functional genomics studies.
  • Apply statistical and computational methods to identify biological mechanisms, therapeutic targets, and treatment responses.
  • Collaborate with biologists, chemists, computational scientists, and cross-functional research teams to translate complex data into actionable insights.
  • Develop reproducible data analysis pipelines using Python and bioinformatics tools.
  • Perform quality control, data integration, visualization, and statistical analysis of large-scale genomics datasets.
  • Integrate multimodal datasets, including single-cell, genomic, and clinical data, to support research and therapeutic development.
  • Present findings through scientific reports, presentations, and collaborations with internal research teams.
  • Maintain well-documented, reproducible computational workflows and contribute to continuous process improvements.
Required Qualifications
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science, Statistics, Mathematics, or a related quantitative life science discipline.
  • Proven experience analyzing large-scale single-cell RNA sequencing (scRNA-seq) datasets.
  • Strong programming skills in Python for scientific computing and data analysis.
  • Solid background in statistics, probabilistic modeling, and computational data analysis.
  • Experience working with next-generation sequencing (NGS) and genomics datasets.
  • Excellent analytical, communication, and problem-solving skills.
  • Demonstrated ability to collaborate effectively in multidisciplinary research environments.
  • Strong publication record demonstrating scientific contributions.
Preferred Qualifications
  • Experience with Perturb-seq, CROP-seq, Sci-Plex, or other CRISPR-based perturbation screening technologies.
  • Experience with CRISPR functional genomics and single-cell perturbation analysis.
  • Knowledge of multimodal data integration, including genomic, transcriptomic, and clinical datasets.
  • Experience using workflow management systems such as Nextflow or Snakemake.
  • Experience working on High Performance Computing (HPC) environments using SLURM.
  • Familiarity with cloud computing, reproducible workflows, and collaborative software development practices.

If interested, please send us your updated resume at

Single Cell Sequencing, Pertub-Seq, Slurm, HPC, Computational Biology

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