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Computational Spatial Transcriptomics Jobs (NOW HIRING)

Valius Sciences

Computational Biologist

San Francisco, CA · On-site

$125K - $185K/yr

Computational biologist role We're hiring a computational biologist to analyze our patients' omics ... Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read ...

Transcripta Bio

Computational Biologist

Palo Alto, CA · On-site

PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of ... Familiarity with spatial transcriptomics or multimodal data integration approaches. * Experience ...

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How much do computational spatial transcriptomics jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for computational spatial transcriptomics in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What are some typical challenges faced when working in computational spatial transcriptomics, and how can new team members prepare for them?

Professionals in computational spatial transcriptomics often encounter challenges related to handling and analyzing large, complex datasets that combine spatial and gene expression information. Integrating data from different technologies and ensuring data quality can be demanding, requiring strong programming skills and familiarity with bioinformatics pipelines. New team members can prepare by strengthening their skills in statistical analysis, programming languages like Python or R, and staying updated on the latest spatial transcriptomics techniques. Collaborating closely with experimental biologists and data scientists is also key to overcoming these challenges and driving successful research outcomes.

What is the difference between Computational Spatial Transcriptomics vs Computational Biologist?

AspectComputational Spatial TranscriptomicsComputational Biologist
Required CredentialsAdvanced degrees in bioinformatics, computational biology, or related fields; experience with spatial data analysisTypically a PhD or Master's in biology, bioinformatics, or related disciplines; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic institutions focusing on spatial genomicsResearch institutions, biotech firms, academia working on biological data analysis
Industry UsageSpecialized in spatial transcriptomics techniques and data interpretationBroad biological data analysis across various fields

Computational Spatial Transcriptomics focuses on analyzing spatial gene expression data within tissues, requiring specialized skills in spatial data processing. In contrast, Computational Biologists work on a wider range of biological data types. While both roles involve bioinformatics expertise, the former emphasizes spatial data analysis techniques specific to transcriptomics.

What is computational spatial transcriptomics?

Computational spatial transcriptomics is a field that combines advanced computational methods with spatial transcriptomics, a technique that measures gene expression within the physical context of tissue samples. It involves processing and analyzing large datasets to map where specific genes are active within tissues, helping researchers understand how cells interact and function in their native environments. This approach is crucial for studies in developmental biology, cancer research, and neuroscience, as it provides insights into cellular organization and tissue architecture. Computational tools help extract meaningful patterns from complex data, enabling discoveries that were previously impossible with traditional methods.

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

To excel in Computational Spatial Transcriptomics, you need a strong background in bioinformatics, genomics, and statistical data analysis, typically supported by advanced degrees in computational biology or related fields. Familiarity with programming languages (such as R and Python), spatial transcriptomics platforms (like 10x Genomics Visium), and high-throughput sequencing data analysis tools is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These competencies ensure accurate data interpretation, innovative research, and successful integration of spatial transcriptomics insights into biological and clinical applications.
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Computational Spatial Transcriptomics jobs near you
Infographic showing various Computational Spatial Transcriptomics job openings in the United States as of June 2026, with employment types broken down into 69% Full Time, 30% Part Time, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Staff Scientist, Spatial AI & Computational Biology

Stellaromics Inc.

Boston, MA

Full-time

Posted 6 days ago

Job description

A biotech startup is seeking a Staff Scientist in Algorithm Development to lead computational methods for spatial transcriptomics in Boston. The ideal candidate will possess a Ph.D. and significant experience in image and signal processing, as well as proficiency in Python and C++.

This role emphasizes innovative computational approaches to accelerate biomedical research and improve product development. #J-18808-Ljbffr

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