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Single Cell Spatial Transcriptomics Jobs in Boston, MA

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How much do single cell spatial transcriptomics jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for single cell spatial transcriptomics in Boston, MA is $23.51, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $29.52 per hour, depending on experience, location, and employer.

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

To thrive as a Single Cell Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree (PhD or MSc) in a relevant field. Familiarity with high-throughput sequencing platforms, spatial transcriptomics technologies (like 10x Genomics Visium or NanoString GeoMx), and data analysis tools such as R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These skills and qualities are vital for generating reliable insights into cellular function and spatial organization, which drive innovative research and discovery.

What are some typical challenges faced by professionals working in Single Cell Spatial Transcriptomics, and how can they be addressed?

Professionals in Single Cell Spatial Transcriptomics often encounter challenges related to handling large, complex data sets and integrating spatial information with single-cell transcriptomic profiles. These tasks demand strong computational skills and close collaboration with bioinformaticians and other researchers. Effective communication within interdisciplinary teams is essential to ensure experimental design aligns with downstream analysis needs. Staying updated with rapidly evolving technologies and best practices also helps professionals overcome technical hurdles and produce reliable, high-impact results.

What is single cell spatial transcriptomics?

Single cell spatial transcriptomics is a cutting-edge technique that allows researchers to analyze gene expression in individual cells while preserving their spatial location within a tissue. This method combines the high-resolution insights of single-cell RNA sequencing with spatial information, enabling scientists to understand how cells interact and organize within their native environments. It is widely used in biomedical research to study tissue architecture, disease mechanisms, and cellular heterogeneity.
What are popular job titles related to Single Cell Spatial Transcriptomics jobs in Boston, MA? For Single Cell Spatial Transcriptomics jobs in Boston, MA, the most frequently searched job titles are:
What cities near Boston, MA are hiring for Single Cell Spatial Transcriptomics jobs? Cities near Boston, MA with the most Single Cell Spatial Transcriptomics job openings:
Postdoctoral Associate - Xavier Lab

Postdoctoral Associate - Xavier Lab

Broad Institute

Cambridge, MA • On-site

$70K - $92K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

General information
Location
Cambridge, MA
Ref #
44291
Job Family
Research
Workplace
On-Site
Date published
06/03/2026
Time Type
Full time
Pay Range
$70,000.00/yr - $92,666.67/yr
Description & Requirements
The Broad Institute of MIT & Harvard is seeking a highly motivated Postdoctoral Associate to join the Xavier Lab and Klarman Cell Observatory and lead data analysis and algorithm development designed to determine the underlying factors contributing to health and disease, with a strong focus on discovering disease mechanisms at the level of their molecular and cellular pathways.
We are an interdisciplinary group with expertise in computational biology, functional genomics, microbiology, and immunology. The candidate for this position will be working closely with computational and experimental biologists, including Principal Investigators, graduate students, and staff scientists in the group. They will contribute by directing, planning, and executing the analyses of large multi-omic datasets with the goal of identifying biological features (e.g., variants, genes, microbes) that are relevant to human health. Prospective applicants should have made significant contributions to their area of study, as evidenced by a strong publication record. We are seeking creative and highly motivated individuals who want to work in a dynamic, multi- disciplinary research environment.
The ideal candidate will be the computational analysis lead for projects discovering the mechanisms behind inflammatory and autoimmune diseases. They should have excellent technical expertise while being driven to make a biological impact. In particular, we are seeking a postdoc to take primary leadership for analyzing spatial and single-cell multiomics datasets collected from human tissue samples as well as mouse models.
Responsibilities
  • Oversee data generation and data analysis across various internal and external collaborations. Includes working datasets such as single-cell RNA-Seq, single-cell ATAC-Seq, spatial transcriptomics, proteomics, metabolomics, and/or microbiome data.
  • Demonstrate flexibility to execute tasks requiring various skill levels and learn new skills as needed.
  • Perform analyses using current processes and identify, propose, and implement improvements to ensure output of high-quality datasets.
  • Work with other team members and leadership to plan project requirements and timelines, shift priorities as needed, and efficiently execute project tasks.
  • Identify and help solve methodological problems, including adjustments to experimental and computational protocols to ensure generation of high-quality datasets suited to answer core biological questions.
  • Use single cell and spatial transcriptomic approaches to understand tissue organization and how they are altered in disease environments such as chronic inflammation.
  • Use a systems medicine approach to understand inflammatory and other diseases.
  • Develop novel methods to facilitate exploration of unstructured datasets.
  • Write well-crafted, maintainable, scalable, and performant code.
  • Lead and carry out projects with minimal supervision.
  • Participate in writing papers and grant proposals.
  • Present project progress during group meetings.

Qualifications
  • Ph.D. in Computational Biology, Computer Science, Physics, Math, Statistics, or related quantitative fields and strong knowledge of a variety of biological areas of research with 0+ years of experience within the field.
  • Scientific and numerical programming in Python or R and knowledge of class ML methods and deep learning methods.
  • Well versed in a variety of bioinformatic analyses, including Next Generation Sequencing pipelines (single-cell RNA-Seq, single-cell ATAC-Seq, spatial transcriptomics analyses etc...).
  • Excellent critical thinking, research, and analytical skills.
  • Excellent communication and interpersonal skills and the ability to work with biologists, computational biologists, data scientists, and software engineers.
  • Must be able to work independently as well as part of a team in a fast-paced, highly collaborative environment.
  • Demonstrated ability to carry out a variety of tasks in parallel, recognize and solve problems effectively, and shift priorities rapidly.

Selected Publications
Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis
https://pubmed.ncbi.nlm.nih.gov/31348891/
The landscape of immune dysregulation in Crohn's disease revealed through single-cell transcriptomic profiling in the ileum and colon
https://pubmed.ncbi.nlm.nih.gov/36720220/
Bidirectional CRISPR screens decode a GLIS3-dependent fibrotic cell circuit
https://pubmed.ncbi.nlm.nih.gov/41501466/
Population-scale multiome immune cell atlas reveals complex disease drivers
https://www.medrxiv.org/content/10.1101/2025.11.25.25340489v1
A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions
https://www.biorxiv.org/content/10.64898/2026.03.31.715361v2.full
Bridging AI and biology: Foundation models meet human physiology and disease
https://pubmed.ncbi.nlm.nih.gov/41519120/
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.
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.