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Computational Spatial Transcriptomics Jobs (NOW HIRING)

Bruker Corporation

Computational Biologist

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Respond to technical inquiries and assist with data quality issues across transcriptomics and ...

Bruker

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Respond to technical inquiries and assist with data quality issues across transcriptomics and ...

UNAVAILABLE

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Respond to technical inquiries and assist with data quality issues across transcriptomics and ...

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Computational Spatial Transcriptomics information

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$40

$54

$74

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.
Scientist II, Clinical Bioinformatics

Scientist II, Clinical Bioinformatics

10x Genomics

Pleasanton, CA • On-site

$123K - $167K/yr

Full-time

Medical, Retirement

Posted 21 days ago

Job description

About The Role
10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Scientist II to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights.
The role requires a biology-first mindset, proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor. The successful candidate will have an opportunity to work with some of the largest biomedical datasets assayed using cutting-edge 10x Genomics technologies, deriving clinical insights that power the next generation of clinical diagnostics.
What You Will Be Doing:
  • Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis.
  • Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets.
  • Design, implement and validate biomarkers for diagnostic applications.
  • Implement and maintain bioinformatics pipelines for reproducible, large-scale data processing.
  • Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.

To Be Successful, You Will Need:
  • Ph.D. in bioinformatics, computational biology, genomics or a related discipline with extensive hands-on experience in single-cell NGS data analysis.
  • A minimum of 2 years of industry experience post Ph.D.
  • Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers.
  • In-depth understanding of the assumptions, limitations and caveats of statistical methods.
  • Experience developing and optimizing high-performance, scalable code.
  • Proficiency working in a Linux environment.
  • Goal-oriented, self-motivated and an independent problem solver.
  • Meticulous attention to detail and a conscientious work ethic.

Preferred Skills
  • Hands-on experience with 10x Genomics single-cell and in-situ transcriptomics technologies is a strong preference
  • Hands-on research experience in cancer or autoimmune diseases is a strong preference
  • Knowledge of clinical genomics, biomarker discovery and diagnostics
  • Development of statistical models and algorithms for single-cell or spatial transcriptomics data
  • Application of machine learning, particularly in the context of genomics
  • Proficiency with workflow orchestration frameworks such as Snakemake, Nextflow or Martian
  • Programming best practices including data analysis reproducibility, version control, design patterns, testing, debugging and profiling
  • Track record of writing production-level code or maintaining published software packages
  • High-throughput computing infrastructure such as HPCs or cloud computing

Below is the base pay range for this full-time position. The actual base pay will depend on several factors unique to each candidate, including one's skills, qualifications, and experience. At 10x, base pay is also just one component of the Company's total compensation package. This role is also eligible for 10x's equity grants, its comprehensive health and retirement benefit programs, and its annual bonus program or sales incentive program. During the hiring process, your 10x recruiter can share more about the Company's total compensation package.
Pay Range
$123,400-$167,000 USD
About 10x Genomics
At 10x Genomics, accelerating our understanding of biology is more than a mission for us. It is a commitment. This is the century of biology, and the breakthroughs we make now have the potential to change the world.
We enable scientists to advance their research, allowing them to address scientific questions they did not even know they could ask. Our tools have enabled fundamental discoveries across biology including cancer, immunology, and neuroscience.
Our teams are empowered and encouraged to follow their passions, pursue new ideas, and perform at their best in an inclusive and dynamic environment. We know that behind every scientific breakthrough, there is a deep infrastructure of talented people driving the life sciences industry and making it possible for scientists and clinicians to make new strides. We are dedicated to finding the very best person for every aspect of our work because the innovations and discoveries that we enable together will lead to better technologies, better treatments, and a better future. Find out how you can make a 10x difference.
Individuals seeking employment at 10x Genomics are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation, or any other characteristic protected by applicable law.
10x does not accept unsolicited applicants submitted by third-party recruiters or agencies. Any resume or application submitted to 10x without a vendor agreement in place will be considered unsolicited and property of 10x, and 10x will not pay a placement fee.
Please be aware of recruitment scams impersonating 10x Genomics. All recruiting communication will come from email addresses @10xgenomics.com. We also want to encourage you to apply to 10x Genomics positions directly on our careers site, Careers.10xgenomics.com or from reputable third party sites, such as LinkedIn or Indeed. We will never request payment or sensitive personal information during the recruiting process.

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