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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 ...

AA2IT

Bioinformatics Scientist - II

Cambridge, MA · On-site

$75/hr

Ph.D. in Computational Biology or closely related field -- no BS/MS-only candidates will be ... Proven work with RNA-Seq, single-cell RNA-Seq, genotype data, spatial transcriptomics, and ...

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Computational Spatial Transcriptomics information

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How much do computational spatial transcriptomics jobs pay per hour?

As of May 28, 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 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.

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 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 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.

More about Computational Spatial Transcriptomics jobs
What cities are hiring for Computational Spatial Transcriptomics jobs? Cities with the most Computational Spatial Transcriptomics job openings:
What states have the most Computational Spatial Transcriptomics jobs? States with the most job openings for Computational Spatial Transcriptomics jobs include:
What job categories do people searching Computational Spatial Transcriptomics jobs look for? The top searched job categories for Computational Spatial Transcriptomics jobs are:
Computational Spatial Transcriptomics jobs near you
Infographic showing various Computational Spatial Transcriptomics job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Computational Biologist

Valius Sciences

San Francisco, CA • On-site

$125K - $185K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 14 days ago

Job description

Valius overview
Valius is building the next generation of precision oncology, helping cancer patients and their physicians make more informed treatment decisions through comprehensive molecular testing and rigorous scientific analysis. In our first nine months, we've worked with close to 50 patients, identifying plausible therapeutic targets in the vast majority of cases. We've just raised a $10M seed round, led by 8VC and Basis Set Ventures, and are looking for folks passionate about changing cancer care to join our growing team.
Computational biologist role
We're hiring a computational biologist to analyze our patients' omics data. This role sits at the intersection of cutting-edge science and real-world clinical impact: you'll apply state-of-the-art omics techniques to complex patient datasets to deliver rigorous, actionable insights.
You'll have significant ownership from day one, including direct exposure to, and regular meetings with, the founding team. As we grow, you'll have the potential to develop into a broader scientific leadership role.
This role will be expected to work out of our beautiful San Francisco office four days a week.
What you'll do
  • Analyze multi-modal omics data. Apply cutting-edge techniques, including scRNAseq, spatial transcriptomics, and long-read sequencing, to derive meaningful insights from complex patient datasets.
  • Deliver patient-facing results. Translate computational findings into clear, rigorous outputs that directly inform treatment decisions for patients and their care teams.
  • Develop and maintain analytical pipelines. Build robust, reproducible workflows that scale with our growing patient programs.
  • Partner with the scientific and clinical teams. Collaborate closely with colleagues across disciplines to ensure analyses are well-designed, well-interpreted, and actionable.
  • Stay at the frontier. Continuously evaluate and incorporate emerging methods in omics and computational biology to keep Valius's science best-in-class.
  • Contribute across the company as needed. In a small team, you may pitch in on cross-functional initiatives as we scale.

What you'll bring
  • Deep fluency in omics analysis, including experience with techniques such as scRNAseq, spatial transcriptomics, or long-read sequencing
  • Strong programming skills in Python and/or R, with experience building reproducible analytical workflows (i.e., Snakemake, Nextflow, Git)
  • Proven ability to move quickly and deliver rigorous results in parallel
  • Clear communicator who can translate complex findings for both scientific and non-scientific audiences
  • High agency and ownership mindset with the ability to see analyses through to actionable conclusions
  • Excited to work in a fast-paced startup environment where flexibility and initiative are valued
  • Commitment to our patient-focused mission
  • Interest in working for a small, early-stage startup

Other nice to haves
  • Experience in oncology or translational research
  • Familiarity with cloud-based computing environments and large-scale data infrastructure
  • Interest in growing into a scientific leadership role as the company scales

What we'll bring
  • Competitive salary and equity compensation
  • Generous refresh grants
  • Comprehensive benefits (health, dental, vision, 401(k))
  • Genuine investment in your professional development

Fun, mission-driven team culture

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