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Postdoc Single Cell Rna Sequencing Analysis Jobs

Washington University of St. Louis

... single cell RNA-sequencing dataset analysis) informs the wet lab work. Primary Duties & Responsibilities: For more information about the Kotov lab, please visit Information on being a postdoc at ...

Washington University of St. Louis

... single-cell RNA sequencing, and epigenetics. We are seeking a highly motivated postdoctoral ... Collaboration, Data Analysis, Data Interpretations, Experimentation, Laboratory Operations ...

New York Genome Center

Research Technician II

Manhattan, NY · On-site

$19.75 - $27.25/hr

Perform single-cell and multi-omic workflows, including single-cell RNA sequencing, single-cell ... Basic familiarity with sequencing quality-control metrics or analysis environments such as R ...

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

As of Aug 29, 2026, the average hourly pay for postdoc single cell rna sequencing analysis in the United States is $22.32, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $24.76 per hour, depending on experience, location, and employer.

What does a postdoc in single cell RNA sequencing analysis do?

A Postdoc in Single Cell RNA Sequencing (scRNA-seq) Analysis specializes in analyzing gene expression data from individual cells. Their main responsibilities include processing raw sequencing data, performing quality control, identifying cell types or states, and interpreting biological insights from the data. They often develop or apply computational methods to handle large datasets, collaborate with experimental biologists, and present findings through publications or conferences. The ultimate goal is to understand cellular heterogeneity and uncover new biological mechanisms at the single-cell level.

What are the key skills and qualifications needed to thrive as a postdoc in single cell RNA sequencing analysis, and why are they important?

To thrive as a Postdoc in Single Cell RNA Sequencing Analysis, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by a PhD in a relevant field. Proficiency with computational tools such as R, Python, and specialized single-cell analysis platforms (e.g., Seurat, Scanpy), as well as experience with data visualization and next-generation sequencing, is essential. Strong problem-solving abilities, effective communication, and collaboration skills help distinguish top candidates in interdisciplinary research environments. These skills enable accurate data interpretation, drive innovation, and support impactful scientific discoveries in complex biological systems.

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

Postdocs in single cell RNA sequencing analysis often encounter challenges such as managing large and complex datasets, integrating multi-omic data, and staying current with rapidly evolving bioinformatics tools. Collaborating closely with wet lab scientists and computational biologists is essential to interpret results accurately and to troubleshoot technical issues. Building strong programming and statistical skills, as well as actively participating in lab meetings and seminars, can help address these challenges and contribute to both personal growth and successful project outcomes.

What is the difference between Postdoc Single Cell Rna Sequencing Analysis vs Postdoc Bioinformatics?

AspectPostdoc Single Cell Rna Sequencing AnalysisPostdoc Bioinformatics
Required CredentialsPhD in Biology, Genetics, or related field; experience in sequencing data analysisPhD in Computer Science, Bioinformatics, or related field; programming skills essential
Work EnvironmentResearch labs focusing on genomics and cell biologyResearch institutions, biotech companies, or academic labs with computational focus
Employer & Industry UsageBiotech, academic research, pharmaceutical companiesBiotech, healthcare, academic research, industry R&D

Postdoc Single Cell Rna Sequencing Analysis specialists focus on analyzing single-cell transcriptomics data, often requiring biological expertise and lab experience. In contrast, Postdoc Bioinformatics roles emphasize computational skills and software development to interpret large datasets across various biological contexts. Both roles are vital in genomics research but differ in their primary focus and skill set.

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Postdoc Single Cell Rna Sequencing Analysis jobs near you
Infographic showing various Postdoc Single Cell Rna Sequencing Analysis job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $46,417 per year, or $22.3 per hour.

Postdoctoral Associate - Bioinformatics

Baylor College of Medicine

Houston, TX

Full-time

Re-posted 23 days ago

Baylor College of Medicine rating

8.0

Company rating: 8.0 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

190th of 627 rated colleges and universities

Job description

Summary

Baylor College of Medicine is seeking a highly motivated Postdoctoral Research Associate for an integrative analysis of transcriptomic, epigenomic, and proteomic large-scale datasets, under the joint supervision of Dr. Cristian Coarfa and Dr. Andrew DiNardo. This is an opportunity for an ambitious scientist committed to advancing their academic career, who demonstrates strong work ethic, exceptional initiative, and an innovative, analytical approach to solving complex scientific problems. The position will involve analysis of DNA methylation, single cell RNA and ATAC sequencing, Fiber-sequencing, and data science approaches to support research aimed at understanding long-term molecular changes induced by infections, in particular tuberculosis and other respiratory infections.

Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

Job Duties
  • Analyzes single cell RNA-Sequencing, single cell ATAC-Seq, CITE-Seq, as well as bulk RNA-Seq, Proteomics, Metabolomics, and other datasets, generated from tuberculosis patient cohorts with rich clinical data.
  • Performs advanced modeling of post-tuberculosis lung disease risk using approaches including generalized linear models and deep learning.
  • Performs other job-related duties as assigned.
Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.
Preferred Qualifications
  • Ph.D. in Computer Science, Bioinformatics, or Biology, with a strong background in statistics and familiarity with large datasets such as proteomics or sequencing.
  • Experience in epigenetics or gene regulation is a plus.
  • Experience with statistical analysis tools such as R or Python is required (Candidates will be expected to pass a basic programming test in Python).
  • Excellent written and verbal English skills, strong communication and interpersonal skills, and the ability to work within large collaborative teams.

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