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How much do single cell spatial transcriptomics jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for single cell spatial transcriptomics in Dallas, TX is $21.41, according to ZipRecruiter salary data. Most workers in this role earn between $16.63 and $26.88 per hour, depending on experience, location, and employer.

What is single cell spatial transcriptomics?

Single cell spatial transcriptomics is a cutting-edge technique that allows researchers to analyze gene expression in individual cells while preserving their spatial location within a tissue. This method combines the high-resolution insights of single-cell RNA sequencing with spatial information, enabling scientists to understand how cells interact and organize within their native environments. It is widely used in biomedical research to study tissue architecture, disease mechanisms, and cellular heterogeneity.

What are the typical challenges faced by professionals working in single cell spatial transcriptomics, and how can they be addressed?

Professionals in Single Cell Spatial Transcriptomics often encounter challenges related to handling large, complex data sets and integrating spatial information with single-cell transcriptomic profiles. These tasks demand strong computational skills and close collaboration with bioinformaticians and other researchers. Effective communication within interdisciplinary teams is essential to ensure experimental design aligns with downstream analysis needs. Staying updated with rapidly evolving technologies and best practices also helps professionals overcome technical hurdles and produce reliable, high-impact results.

What are the key skills and qualifications needed to thrive as a single cell spatial transcriptomics scientist, and why are they important?

To thrive as a Single Cell Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree (PhD or MSc) in a relevant field. Familiarity with high-throughput sequencing platforms, spatial transcriptomics technologies (like 10x Genomics Visium or NanoString GeoMx), and data analysis tools such as R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These skills and qualities are vital for generating reliable insights into cellular function and spatial organization, which drive innovative research and discovery.

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What cities near Dallas, TX are hiring for Single Cell Spatial Transcriptomics jobs?

Cities near Dallas, TX with the most Single Cell Spatial Transcriptomics job openings:

Single Cell Spatial Transcriptomics jobs near you
Infographic showing various Single Cell Spatial Transcriptomics job openings in Dallas, TX as of August 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 78% Full Time, 16% Part Time, and 4% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $44,537 per year, or $21.4 per hour.

POSTDOCTORAL RESEARCHER-Biomedical Data Science & AI-Epidemiology-Ruan Lab [Req#: 963199, Position#:

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Posted 15 days ago

UT Southwestern rating

7.9

Company rating: 7.9 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

107th of 888 rated healthcare providers

Job description

Description
POSTDOCTORAL RESEARCHER
A postdoctoral fellow position is now available in the laboratories of Dr. Peifeng Ruan (https://qbrc.swmed.edu/labs/ruanlab/) at the Quantitative Biomedical Research Center (QBRC) in the Peter O'Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas. The labs' research focuses on developing and applying advanced computational and AI methods to address critical challenges in biomedical research and clinical practice.
The training activities of this position will include data management, curation, and analysis of large-scale biomedical and clinical datasets, including proteomics, metabolomics, single-cell transcriptomics and spatial transcriptomics data; development and/or implementation of novel statistics, machine learning and AI approaches; integration of molecular, cellular, spatial, imaging, and clinical data; interpretation and presentation of analysis results; and writing manuscripts. We are actively seeking exceptionally motivated individuals with outstanding problem-solving abilities. In this role, you will conduct cutting-edge research at the intersection of artificial intelligence and biomedical sciences, with opportunities to collaborate with clinical investigators and industry partners.
Information on our postdoctoral training program, benefits, and a virtual tour can be found at https://www.utsouthwestern.edu/research/postdoctoral-scholars/.
Qualifications
Candidates with a Ph.D. in computer science, bioinformatics, data science, machine learning, or a related quantitative field are encouraged to apply. Experience with one or more of the following areas is desirable: single-cell transcriptomics and spatial transcriptomics, knowledge graphs, large language models, or analysis of real-world clinical data (e.g., electronic health records, claims databases, or pharmacovigilance databases).
Application Instructions
Interested individuals should send a CV and a list of three references to:
Peifeng Ruan
Peifeng.Ruan@UTSouthwestern.edu

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