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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 ...

UMass Med School

Computational Biologist

Worcester, MA · On-site

$90K/yr

Computational Biologist Minimum Salary US-MA-Worcester Job Location 2 days ago(7/10/2026 9:17 AM ... spatial transcriptomics. * Develop new analysis methods as needed and as they arise during ...

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How much do computational spatial transcriptomics jobs pay per hour?

As of Jul 14, 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
Immunology Senior Research Scientist - Spatial Transcriptomics

Immunology Senior Research Scientist - Spatial Transcriptomics

Vertex Pharmaceuticals

Seattle, WA • On-site

$124K - $186K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

Job Description
At Vertex, we invest in scientific innovation to create transformative medicines for people with serious diseases. Our growing Molecular Profiling team is seeking a Senior Scientist, Spatial Transcriptomics to provide scientific and deep technical expertise in spatial biology to support discovery, translational, and development programs. This role will be instrumental in driving mechanistic insights into disease biology, tissue microenvironments, and therapeutic response through spatial profiling of gene expression in tissue context.
The ideal candidate will bring deep expertise in spatial transcriptomics, tissue-based molecular profiling, experimental design, and data interpretation, along with strong cross-functional collaboration skills and a passion for technical innovation.
Key Duties and Responsibilities:
  • Lead the design, execution, and optimization of spatial transcriptomics studies to address key biological questions in disease-relevant tissues and model systems
  • Lead efforts to characterize tissue architecture, cellular microenvironments, cell-cell interactions, and spatial organization of biological processes
  • Generate and interpret high-quality spatial data to derive biological insights that support disease biology, target biology, mechanism of action, and biomarker strategies
  • Integrate spatial transcriptomics data with complementary datasets, including single-cell RNA-seq, proteomics, imaging, histology, and other molecular profiling approaches to enable multi-modal biological insights
  • Develop, validate, and implement robust workflows for sample preparation, assay execution, quality control, and data review
  • Evaluate and apply emerging spatial biology technologies to expand research capabilities and enable innovative scientific applications
  • Drive adoption of best practices and contribute to establishing robust spatial biology workflows and standards across the team
  • Partner closely with cross-functional teams across disease biology, pharmacology, translational medicine, biomarker sciences, bioinformatics, and clinical development to inform study design, data interpretation, and program strategy
  • Contribute to internal scientific strategy through clear communication of results, technical recommendations, and experimental insights
  • Prepare technical documentation, protocols, study summaries, and presentations
  • Mentor junior scientists and help build a collaborative, high-performing team environment

Knowledge and Skills:
  • Deep expertise in spatial transcriptomics and tissue-based molecular profiling
  • Strong understanding of transcriptomics, RNA biology, tissue architecture, and cellular heterogeneity
  • Experience with fresh frozen and FFPE tissue processing, tissue quality assessment, and assay optimization
  • Familiarity with one or more spatial biology platforms, including sequencing-based and imaging-based technologies
  • Experience integrating spatial data with single-cell, proteomic, imaging, and histologic datasets
  • Working knowledge of computational approaches for spatial data analysis, visualization, and interpretation, including proficiency in R and/or Python and familiarity with relevant analysis tools and workflows
  • Strong experimental rigor, problem-solving ability, and attention to data quality and reproducibility
  • Excellent communication skills and ability to work effectively in a matrixed, multidisciplinary environment

Education and Experience:
  • PhD in Immunology, Cell Biology, Molecular Biology, Biology, Biomedical Sciences, or related discipline with 2+ years of relevant experience; or
  • Master's degree with 6+ years of relevant experience; or
  • Bachelor's degree with 8+ years of relevant experience

Preferred Qualifications:
  • Hands-on experience with one or more spatial transcriptomics platforms (e.g., sequencing-based or imaging-based such as 10x Genomics Visium, Nanostring CosMx or similar technologies)
  • Experience with histology, immunofluorescence, image analysis, and multiplexed tissue profiling
  • Experience supporting drug discovery, translational research, or clinical biomarker development, ideally in immunology or inflammation
  • Familiarity with single-cell RNA-seq analysis and integration of multi-omics datasets
  • Experience in immunology and inflammation disease areas
  • Knowledge of spatial proteomics or broader tissue-based profiling approaches

Pay Range:
$124,200 - $186,400
Disclosure Statement:
The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.
At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.
Flex Designation:
On-Site Designated
Flex Eligibility Status:
In this On-Site designated role, you will work five days per week on-site with ad hoc flexibility.
Note: The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.
#LI-Onsite
Company Information
Vertex is a global biotechnology company that invests in scientific innovation.
Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.
Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com

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