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Computational Spatial Transcriptomics Jobs in Boston, MA

Massgeneralbrigham

Computational Associate

Boston, MA · On-site

Experience analyzing genomics, RNA sequencing, spatial transcriptomics, single-cell, or epigenomic ... Gain hands-on experience with advanced computational and translational research methodologies.

Jj

Principal Scientist, Spatial Omics

Cambridge, MA

... computational literacy to understand experimental data flows and interface effectively with bioinformatics and data science teams. Experience with spatial transcriptomics, genetic library design ...

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How much do computational spatial transcriptomics jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for computational spatial transcriptomics in Boston, MA is $59.67, according to ZipRecruiter salary data. Most workers in this role earn between $50.91 and $79.90 per hour, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Computational Spatial Transcriptomics jobs in Boston, MA?

For Computational Spatial Transcriptomics jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Computational Spatial Transcriptomics jobs in Boston, MA look for?

The top searched job categories for Computational Spatial Transcriptomics jobs in Boston, MA are:

What cities near Boston, MA are hiring for Computational Spatial Transcriptomics jobs?

Cities near Boston, MA with the most Computational Spatial Transcriptomics job openings:

Computational Spatial Transcriptomics jobs near you
Infographic showing various Computational Spatial Transcriptomics job openings in Boston, MA as of August 2026, with employment types broken down into 1% Internship, 57% Full Time, 39% Part Time, and 3% Contract. Highlights an 58% Physical, 2% Hybrid, and 40% Remote job distribution, with an average salary of $124,121 per year, or $59.7 per hour.

Technician I or II - Spatial Omics/MERFISH- Sun Lab (Relocation Assistance Available)

Whitehead Institute

Cambridge, MA • On-site

$55K/yr

Full-time

Posted 19 days ago

Job description

Classification:

Exempt

Job Family:

Technicians

Reports to:

AI Whitehead Fellow

Job Description Summary:

OVERALL RESPONSIBILITY
Collaborate on short- and long-term research projects to support the scientific objectives of the laboratory. Perform spatial transcriptomics experiments and associated molecular biology procedures, with a focus on MERFISH and related technologies. Support the development, optimization, and execution of imaging-based transcriptomics workflows and associated data preprocessing pipelines, ensuring high-quality experimental data generation that supports computational modeling and biological discovery. Depending on experience level, the technician may contribute to protocol development, computational workflows, and experimental design.
RESEARCH BACKGROUND AND GOALS
The Sun Lab seeks a highly motivated Spatial Omics Technician interested in combining experimental biology (80%) with computational analysis (20%). Our research focuses on understanding how cells communicate and organize within tissues using large-scale spatial transcriptomics and single-cell genomics technologies.
The successful candidate will contribute to establishing and scaling MERFISH-based experiments, including probe design, tissue processing, imaging workflows, and data preprocessing. This position provides opportunities for hands-on training with cutting-edge spatial transcriptomics technologies for early career candidates, while offering experienced candidates the opportunity to independently optimize workflows and contribute to technology development in close collaboration with computational researchers developing AI models to interpret these datasets.

CHARACTERISTIC DUTIES

  • Perform spatial transcriptomics experiments, including MERFISH sample preparation, hybridization, and imaging workflows
  • Prepare tissue samples (e.g., cryosectioning, fixation, staining) for spatial transcriptomics experiments
  • Assist with or perform probe design and optimization for MERFISH and related spatial technologies
  • Assist with, run, and maintain spatial transcriptomics preprocessing pipelines, including decoding, segmentation, and quality control
  • Organize and manage spatial imaging datasets and associated metadata
  • Develop, implement or modify or implement scripts for probe design, data preprocessing, and quality assessment, as appropriate based on experience
  • Work closely with computational team members to ensure data compatibility with downstream analysis pipelines
  • Maintain detailed experimental documentation and protocols
  • Present experimental progress and results to lab members and collaborators
  • Contribute to the development and optimization of experimental workflows, consistent with experience and level of responsibility

QUALIFICATIONS

  • BSc or MSc (or equivalent) in Molecular Biology, Bioengineering, Genomics, Bioinformatics, or a related field
  • Experience with molecular biology techniques such as RNA handling, hybridization assays, or microscopy
  • Experience with spatial transcriptomics technologies (e.g., MERFISH, Xenium, Slide-seq, seqFISH, or related platforms) is preferred for more experienced candidates but not required for entry-level
  • For Technical Assistant II level candidates: Demonstrated experience independently performing complex molecular biology workflows, troubleshooting experiments, optimizing protocols, and/or working with computational or image analysis pipelines is preferred
  • Basic programming or scripting experience (e.g., Python, R, or MATLAB) is preferred
  • Experience with image analysis or bioinformatics tools is a plus
  • Strong organizational and problem-solving skills
  • Ability to work independently and collaboratively in an interdisciplinary research environment
  • Excellent communication skills and attention to detail

The title (Technician I or Technician II) will be determined based on the candidate's education, prior experience, technical expertise, and demonstrated independence.

Whitehead provides pay ranges representing its good faith estimate of what the Institute reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, and internal peer equity. This pay range represents base pay only and does not include any other benefits or compensation.

  • Pay Range Minimum: $47,500

  • Pay Range Maximum: $55,000


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