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Postdoc Single Cell Rna Sequencing Analysis Jobs in Warren, MA

UMass Med School

Computational Biologist

Worcester, MA · On-site

$90K/yr

Process, analyze, and interpret large-scale datasets including bulk and single-cell RNA-seq, ATAC-seq, proteomics, and spatial transcriptomics. * Develop new analysis methods as needed and as they ...

UMass Med School

Post Doc - Open Rank

Worcester, MA · On-site

$75K/yr

Generate and analyze single-cell transcriptomic, epigenomic, and multi-omic datasets. * Prioritize ... Next Generation Sequencing approaches, such as ATACseq, ChiPseq, RNAseq, single cell-omics.

UMass Med School

Post Doc - Open Rank

Worcester, MA · On-site

$48K - $66K/yr

... postdoctoral researcher will have access to a rich resource of single-cell, spatial, and ... analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) * Strong programming skills in R or ...

UMass Med School

Research Associate II

Worcester, MA · On-site

$47K/yr

... sequencing, single-cell genomics, and immunology to develop stem cell-derived islets that resist ... RNA-seq, ATAC-seq, ChIP-seq, or single-cell omics. * Flow cytometry, imaging, or immune-cell assays.

UMass Med School

Post Doc - Open Rank

Worcester, MA · On-site

$75K/yr

Additional Information Postdoc in Causal Inference of Complex Gene Networks We invite applications ... We approach single-cell biology as a high-dimensional, dynamic, networked system , applying ...

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Postdoc Single Cell Rna Sequencing Analysis information

See Warren, MA salary details

$5

$23

$30

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

As of Aug 11, 2026, the average hourly pay for postdoc single cell rna sequencing analysis in Warren, MA is $23.12, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $25.67 per hour, depending on experience, location, and employer.

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.

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 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 cities near Warren, MA are hiring for Postdoc Single Cell Rna Sequencing Analysis jobs? Cities near Warren, MA with the most Postdoc Single Cell Rna Sequencing Analysis job openings:
Postdoc Single Cell Rna Sequencing Analysis jobs near you
Infographic showing various Postdoc Single Cell Rna Sequencing Analysis job openings in Warren, MA as of August 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 100% In-person job distribution, with an average salary of $48,092 per year, or $23.1 per hour.

Post Doc - Open Rank

University of Massachusetts Medical School

Worcester, MA • On-site

$62K - $75K/yr

Full-time

Re-posted 9 days ago

Job description

Overview
General Summary of the Position
Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865). The Zhou Lab at UMass Chan Medical School (UMass Chan) develops and applies cutting-edge computational and big-data approaches to understand the genomics, epigenomics, and regulatory functions of noncoding RNAs in human disease. We develop computational methods and scalable pipelines to decode noncoding RNAs and their epigenetic modifications from diverse high-throughput sequencing data, including bulk, single-cell, and long-read sequencing data.
Lab Research:
• AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in human genetics and disease, toward developing RNA-based therapeutics.
• Integrative Analysis of Multi-Omics Data: Build end-to-end workflows for bulk and single-cell RNA-seq, long-read sequencing, and epigenomic assays, enabling efficient processing of large-scale multi-omics datasets, and apply them to decipher human diseases.
• Translational Discovery: Integrate computational findings with clinical and genetic data using machine learning/deep learning methods to identify RNA signatures of disease, guiding the development of RNA-based diagnostics and precision-medicine strategies.
The successful candidate will benefit from collaboration with world-class scientists and physicians at UMass Medical Center and in the Greater Boston area, including Harvard/MIT and other prestigious institutes. Dr. Zhou provides tailored mentorship and resources to align postdoctoral training with career goals, whether in academia, industry, or beyond.
Qualifications
REQUIRED QUALIFICATIONS:
  • Ph.D. (or imminent defense) in Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Statistics, Biophysics, Biomedical Engineering, or a related field.
  • Strong programming skills in at least one of: Python, R, C/C++, or Perl; proficient with Unix/Linux.
  • Experience with deep learning, statistical modeling, or AI applications to biological data.
  • Familiarity with transcriptomic technologies, ideally single-cell RNA-seq or long-read sequencing.
  • Demonstrated ability to conduct independent research and publish as first/co-author.
  • Excellent communication, teamwork, and project-management skills.

Additional Information
Application Instructions
Please email the following to Dr. Chan Zhou at chan.zhou@umassmed.edu (subject line: "Postdoc Application - Your Name"):
  1. Cover Letter: Summarize your research background, interests, and career objectives.
  2. Curriculum Vitae: Include publication list and detailed computational skill set.
  3. References: Contact information for at least two referees (email and phone).

Equal Opportunity Employer
UMass Chan Medical School is committed to fostering a diverse and inclusive environment. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
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