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Postdoc Single Cell Rna Sequencing Analysis Jobs in Houston, TX

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX

$46K - $63K/yr

Postdoc will gain an invaluable experience in translational cancer research and the development of ... single-cell sequencing, spatial biology, or transcriptomic analyses. • Experience with ...

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX

$46K - $63K/yr

Postdoc will gain an invaluable experience in translational cancer research and the development of ... single-cell sequencing, spatial biology, or transcriptomic analyses. • Experience with ...

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX · On-site

$46K - $63K/yr

Postdoc will gain an invaluable experience in translational cancer research and the development of ... functional genomics, single-cell sequencing, spatial biology, or transcriptomic analyses.

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellow position is currently available in the lab of Dr. Kristen Pauken in the ... Prior experience with high-dimensional single cell RNA sequencing data analysis and data ...

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellow position is currently available in the lab of Dr. Kristen Pauken in the ... single cell RNA sequencing data analysis and data visualization software is a must. Additionally ...

MD Anderson

Postdoctoral Fellow - Immunology

Houston, TX

$46K - $63K/yr

A postdoctoral fellow position is currently available in the lab of Dr. Kristen Pauken in the ... single cell RNA sequencing data analysis and data visualization software is a must. Additionally ...

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All JobsPostdoc Single Cell Rna Sequencing Analysis JobsPostdoc Single Cell Rna Sequencing Analysis Jobs in Houston, TX

Postdoc Single Cell Rna Sequencing Analysis information

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

As of Aug 19, 2026, the average hourly pay for postdoc single cell rna sequencing analysis in Houston, TX is $21.31, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $23.65 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.

What are popular job titles related to Postdoc Single Cell Rna Sequencing Analysis jobs in Houston, TX?

For Postdoc Single Cell Rna Sequencing Analysis jobs in Houston, TX, the most frequently searched job titles are:

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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 Houston, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $44,327 per year, or $21.3 per hour.

Postdoctoral Associate - AI for Brain Tumors

Baylor College of Medicine

Houston, TX • On-site

$62K/yr

Full-time

Re-posted 26 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

188th of 619 rated colleges and universities

Job description

Postdoctoral Associate - AI for Brain Tumors
Division: Neurosurgery
Work Arrangement: Onsite only
Location: Houston, TX
Salary Range: $62,232
FLSA Status: Exempt
Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.
Summary
The Postdoctoral Associate will develop next-generation AI models for large-scale perturbation modeling in brain tumors. The project will involve building and applying state-of-the-art machine learning approaches, including foundation models, variational autoencoders (VAEs), and transformer-based architectures, to integrate single-cell and multi-omic datasets. The goal is to decode tumor cellular heterogeneity and tumor microenvironment interactions, and to identify targetable genes, pathways, and therapeutic strategies at single-cell resolution.
Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.
Job Duties
  • Develops and implements AI models for perturbation prediction:
    • Designs, trains, and evaluates machine learning models (e.g., transformer-based architectures, VAEs, and foundation models) to predict cellular responses to genetic and pharmacologic perturbations. This includes preprocessing large-scale single-cell and multi-omic datasets, defining model architectures, optimizing training pipelines on GPU clusters, and benchmarking against existing methods.
  • Integrate and analyze large-scale single-cell and multi-omic:
    • Processes and harmonizes scRNA-seq, scATAC-seq, and related datasets across brain tumor cohorts.
    • Performs downstream analyses such as cell state annotation, pathway enrichment, and tumor-tumor microenvironment interaction modeling to generate biologically meaningful insights.
  • Leads computational research projects and method development.
  • 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 Computational Biology, Bioinformatics, Computer Science or a related quantitative field.
  • Strong background in machine learning and statistical modeling, with experience in deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with modern architectures such as transformers, variational autoencoders (VAEs), and foundation models is highly desirable.
  • Experience in analyzing large-scale genomics or single-cell datasets (e.g., scRNA-seq, scATAC-seq).
  • Proficiency in Python and experience with R/Seurat or Scanpy.
  • Strong skills in writing efficient, reproducible, and well-documented code.
  • Evidence of productivity through first-author publications or preprints in computational biology, machine learning, or related fields.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
PD; SN
Requisition ID: 24929

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