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Spatial Transcriptomics Jobs in Boston, MA (NOW HIRING)

Clinical Data Manager

Burlington, MA · On-site

$145K - $160K/yr

We combine cutting-edge technologies including optogenetics, in vivo physiology, and spatial transcriptomics to identify novel drug targets and develop effective therapies to address psychiatric ...

Corporate Controller

Waltham, MA · On-site

$150K - $215K/yr

The company's groundbreaking MERSCOPE product utilizes MERFISH spatial transcriptomics technology to image RNA molecules with high accuracy and unrivaled detection efficiency at subcellular ...

... spatial transcriptomics, methylation, imaging) * Credible as a thought partner with senior R&D leaders on patient-centered prediction topics; able to engage across both scientific and business ...

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Showing results 1-20

Spatial Transcriptomics information

See Boston, MA salary details

$53.2K

$221K

$434.6K

How much do spatial transcriptomics jobs pay per year?

As of Jul 14, 2026, the average yearly pay for spatial transcriptomics in Boston, MA is $221,048.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $434,600.00 per year, depending on experience, location, and employer.

What is spatial transcriptomics?

Spatial transcriptomics is an advanced technique that allows scientists to measure gene expression within the spatial context of tissue samples. Unlike traditional RNA sequencing, which loses information about where each gene is expressed, spatial transcriptomics preserves the physical location of gene activity in tissues. This helps researchers better understand how cells function within their native environments and interact with neighboring cells, which is especially valuable in fields like cancer research, neuroscience, and developmental biology. The method combines microscopy, molecular biology, and computational analysis to produce detailed maps of gene expression.

What are some common challenges faced by professionals working in spatial transcriptomics, and how can they be addressed?

Professionals in spatial transcriptomics often encounter challenges related to handling large, complex datasets and integrating spatial information with gene expression data. Ensuring high-quality sample preparation and mastering advanced imaging or sequencing technologies are also frequent hurdles. These challenges can be addressed by collaborating closely with multidisciplinary teams—including bioinformaticians, molecular biologists, and imaging specialists—and staying up-to-date with the latest software tools and protocols. Continuous learning and effective communication within the team are key to overcoming technical and analytical obstacles in this rapidly evolving field.

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

To thrive as a Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a life science field. Familiarity with spatial transcriptomics platforms (such as 10x Genomics Visium), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating on interdisciplinary research projects. These skills and qualities are crucial for generating high-quality spatial gene expression data and translating findings into meaningful biological insights.
What job categories do people searching Spatial Transcriptomics jobs in Boston, MA look for? The top searched job categories for Spatial Transcriptomics jobs in Boston, MA are:
What cities near Boston, MA are hiring for Spatial Transcriptomics jobs? Cities near Boston, MA with the most Spatial Transcriptomics job openings:
Infographic showing various Spatial Transcriptomics job openings in Boston, MA as of July 2026, with employment types broken down into 72% Full Time, 26% Part Time, 1% Temporary, and 1% Contract. Highlights an 75% Physical, 1% Hybrid, and 24% Remote job distribution, with an average salary of $221,048 per year, or $106.3 per hour.
Postdoctoral Associate - The Getz Lab

Postdoctoral Associate - The Getz Lab

Broad Institute

Cambridge, MA • On-site

$70K - $92K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

General information
Location
Cambridge, MA
Ref #
43959
Job Family
Research
Workplace
On-Site
Date published
07/10/2026
Time Type
Full time
Pay Range
$70,000.00/yr - $92,666.67/yr
Description & Requirements
Overview: The Getz Lab (at the Broad Institute and MGH) is a world-leading laboratory for cancer genome analysis. We develop highly innovative, robust, and widely-used computational methods to study the molecular basis of cancer, including genomic alterations that drive primary and resistant tumors, cell-of-origin, premalignant lesions, mutational processes, activity of different pathways, and microenvironmental changes. We then follow up key findings experimentally. While the comprehensive analysis of cancer genomes is ongoing, major barriers still exist in converting this information to patient benefit and achieving the goal of personalized medicine.
Our work stands at the forefront of cancer genome science, and our research is regularly published in top-tier journals (see our work on Google Scholar and PubMed). We are dedicated to innovating and pushing the limits of what we know and what can be known in understanding the complexities of human cancer.
Environment/Lab Culture: We are an interdisciplinary group of scientists, engineers, and clinicians who work together in a mutually supportive and respectful environment. Ideas are freely shared, and contributions are highly valued.
Moreover, Dr. Getz places a high priority on mentoring postdoctoral trainees to work toward achieving their career paths and goals, and his lab, as well as the environments at the Broad Institute and Massachusetts General Hospital, provide frequent and varied educational and skill-building opportunities.
The lab is engaged in the larger Boston-area ecosystem and the cancer research community worldwide, and provides a vibrant research environment for your contributions to be disseminated and recognized in the field. Our ability to integrate both computational and wet-lab work enables us to address key questions at a deeper and more impactful level. Indeed, we constantly use and develop new technologies to help unlock new findings.
Our ideal postdoc candidate: We are seeking a highly motivated researcher to be the computational analysis lead for projects exploring the mechanisms underlying disease initiation, progression, and/or relapse in multiple myeloma. In particular, we are seeking a postdoc to take primary leadership for analyzing spatial multi-omics data within ongoing projects studying multiple myeloma patient cohorts (e.g., spatial transcriptomics, single-cell spatial proteomics, digital pathology, etc.). These projects will be conducted in close collaboration with Dr. Irene Ghobrial's lab, a world-leading lab in multiple myeloma research at DFCI.
As a member of our team, you will collaborate with other scientists, engineers, and clinicians in a collegial work environment with an emphasis on intellectual rigor. Indeed, our collective brainpower and creativity--our best asset--creates an excellent environment for deep innovation, out-of-the-box thinking, and creative problem solving. We will teach you what you do not yet know through mentoring, peer support, and many educational opportunities (e.g., floor talks, regular meetings, boot camps, journal clubs, conferences, etc.), and we will work together to make discoveries that help answer the most challenging questions in cancer.
The successful candidate will bring strong computational and statistical skills (e.g., a background in Computational Biology, Biology, Machine Learning, Statistics, Medicine, Physics, Chemistry, Engineering, Mathematics, Computer Science, or other related fields) to the lab as well as enthusiasm for learning on the job. In return, you will develop many core competencies to prepare you for the next stages of your career. Come and bring your energy, intellectual curiosity, and computational skills/talents to this world-class dynamic team!
Role Expectations
  • Play a lead role in designing and executing data analysis strategies to support research projects, especially pertaining to spatial multiomics-omics data.
  • Serve as a lead in the project, driving the project's scientific vision, identifying key biological questions and spearheading the computational strategies necessary to address them.
  • Explore and develop tools for analyzing novel data types.
  • Develop new spatial and genomic analysis methodologies for integrating data and predicting tumor outcome, subtypes, molecular mechanisms, and response to therapy.
  • Conceive, implement and test statistical models; analyze data from experiments.
  • Present results to a variety of audiences, including non-computational researchers.
  • Prepare written reports (e.g., manuscripts, grants, patents) and presentations for meetings.
  • Opportunity to teach and mentor junior team members.

Requirements
  • A PhD in Bioinformatics, Computer Science, Machine Learning, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline.
  • 0-1+ years of post-graduate experience.
  • Experience with computational analysis, algorithm development, and statistics.
  • Sufficient hands on experience in methods to analyze spatial multi-omic data is required; experience in analyzing data from other emerging technologies is a plus.
  • Familiarity with a wide variety of bioinformatic analyses, including analyses of data from single-cell RNA sequencing (scRNA-seq), immune BCR/TCR sequencing, and bulk- and single-cell whole-genome sequencing (WGS)
  • Proficiency in at least one modern programming language. Experience with a scientific programming environment (such as Python, R, or Matlab) is preferred.
  • Demonstrated experience with conducting rigorous and reproducible research in a fast-paced environment
  • Highly collaborative, with ability able to work on projects alongside fellow bioinformaticians, wet-lab experimentalists, and clinicians.
  • Strong oral and written communication skills.
  • Fast learner, analytical thinker, creative, hands-on, team-player
  • Background in machine learning or biology is a plus.
  • Knowledge of cancer genomics is a plus but is NOT required. Inclination to acquire such knowledge is imperative.

The expected base pay range for this position as listed above is based on a 40 hour per week schedule. Broad provides pay ranges representing its reasonable and good faith estimate of what the organization reasonably expects to pay for a position at the time of posting. Actual compensation will vary based on factors including but not limited to, relevant skills, experience, education, qualifications, and other factors permissible by law.
At Broad, your base pay is just one part of a comprehensive total rewards package. From day one, this role offers a competitive benefits package including medical, dental, vision, life, and disability insurance; a 401(k) retirement plan; flexible spending and health savings accounts; at least 13 paid holidays; winter closure; paid time off; parental and family care leave; and an employee assistance program, among other Broad benefits.
The Broad Institute is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, disability, protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
Should you need a reasonable accommodation to complete the application or interview process, please contact recruiting@broadinstitute.org for assistance.