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Spatial Transcriptomics information

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$46.8K

$194.3K

$382K

How much do spatial transcriptomics jobs pay per year?

As of Jun 24, 2026, the average yearly pay for spatial transcriptomics in Houston, TX is $194,306.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $382,000.00 per year, depending on experience, location, and employer.

What is spatial transcriptomics?

Spatial transcriptomics is an advanced technique that allows scientists to measure gene expression within the spatial context of tissue samples. Unlike traditional RNA sequencing, which loses information about where each gene is expressed, spatial transcriptomics preserves the physical location of gene activity in tissues. This helps researchers better understand how cells function within their native environments and interact with neighboring cells, which is especially valuable in fields like cancer research, neuroscience, and developmental biology. The method combines microscopy, molecular biology, and computational analysis to produce detailed maps of gene expression.

What are some common challenges faced by professionals working in spatial transcriptomics, and how can they be addressed?

Professionals in spatial transcriptomics often encounter challenges related to handling large, complex datasets and integrating spatial information with gene expression data. Ensuring high-quality sample preparation and mastering advanced imaging or sequencing technologies are also frequent hurdles. These challenges can be addressed by collaborating closely with multidisciplinary teams—including bioinformaticians, molecular biologists, and imaging specialists—and staying up-to-date with the latest software tools and protocols. Continuous learning and effective communication within the team are key to overcoming technical and analytical obstacles in this rapidly evolving field.

What are the key skills and qualifications needed to thrive as a Spatial Transcriptomics Scientist, and why are they important?

To thrive as a Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a life science field. Familiarity with spatial transcriptomics platforms (such as 10x Genomics Visium), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating on interdisciplinary research projects. These skills and qualities are crucial for generating high-quality spatial gene expression data and translating findings into meaningful biological insights.
What are popular job titles related to Spatial Transcriptomics jobs in Houston, TX? For Spatial Transcriptomics jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics jobs in Houston, TX look for? The top searched job categories for Spatial Transcriptomics jobs in Houston, TX are:
What cities near Houston, TX are hiring for Spatial Transcriptomics jobs? Cities near Houston, TX with the most Spatial Transcriptomics job openings:
Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in Houston, TX as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 27% Full Time, 66% Part Time, 4% Contract, and 1% Nights. Highlights an 77% Physical, 1% Hybrid, and 22% Remote job distribution, with an average salary of $194,306 per year, or $93.4 per hour.
Postdoctoral Associate

Postdoctoral Associate

Baylor College of Medicine

Houston, TX • On-site

Full-time

Posted 26 days ago

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

52nd of 539 rated colleges and universities

Job description

Summary

The Cheng Lab in the Department of Medicine, Section of Epidemiology & Population Sciences is searching for highly motivated and talented Postdoctoral Associate to work on Bioinformatics and Computational Biology in Cancer Genomics and Immunology.  This position will be involved in the development and/or application of computational approaches to understand the mechanism of cancer development, progression, metastasis, and prognosis.  The Postdoc should have experience in processing and analyzing data from the next-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable. The Postdoc is expected to collaborate closely with experimental biologists and clinicians. The position offers an extraordinary team-based science environment with opportunities for significant education, training, and career development. The role includes designing analyses, interpreting complex datasets, and translating findings into biologically meaningful insights within a multidisciplinary research environment.  This position offers a highly collaborative, team-based setting with opportunities for advanced training, mentorship, and career development.

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

Job Duties
  • Develops and/or applies computational approaches to understand the mechanism of cancer development, progression, metastasis, and prognosis.
  • Collaborates closely with experimental biologists and clinicians to design studies, validates computational findings, and supports translational applications of research discoveries.
  • Participates in regular joint meetings to present findings, discuss ongoing projects, and align research strategies with lab and departmental priorities.
  • Assists in mentoring and training of junior researchers in computational techniques and bioinformatics best practices.
  • Translates complex computational results into biologically meaningful insights in collaboration with wet-lab teams.
  • Maintains thorough documentation of analyses, pipelines, and datasets in version-controlled environments.
  • Collaborates with experimental biologists and clinicians to apply computational and bioinformatics approaches to study cancer development, progression, metastasis, and prognosis.
  • 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
  • PhD in Computational Biology, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology).
  • Knowledge of basic molecular biology, genomics, and epigenetics.
  • Experience in processing and analyzing data from the next-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). 
  • Experience in both Bioinformatics/Genomics and Cancer Biology is desirable.
  • Experience in the application and development of computational methods/tools or machine learning algorithms.
  • Good computer programming skills in R/Matlab/PerlPython.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

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