Single Cell Spatial Transcriptomics information
See Boston, MA salary details
$13.84 - $15.55
3% of jobs
$15.55 - $17.26
6% of jobs
$18.23 is the 25th percentile. Wages below this are outliers.
$17.26 - $18.97
27% of jobs
The median wage is $20.50 / hr.
$18.97 - $20.68
15% of jobs
$20.68 - $22.39
9% of jobs
$22.39 - $24.10
0% of jobs
$24.10 - $25.81
1% of jobs
$25.81 - $27.52
6% of jobs
$28.70 is the 75th percentile. Wages above this are outliers.
$27.52 - $29.23
9% of jobs
$29.23 - $30.93
9% of jobs
$30.93 - $32.64
13% of jobs
How much do single cell spatial transcriptomics jobs pay per hour?
As of Aug 17, 2026, the average hourly pay for single cell spatial transcriptomics in Boston, MA is $23.51, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $29.52 per hour, depending on experience, location, and employer.
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.
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.
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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