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Computational Spatial Transcriptomics Jobs in Peabody, MA

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

Postdoctoral Fellow

Cambridge, MA · On-site

$67K - $80K/yr

This person will develop new computational methods to analyze novel RNAseq, ATACseq, and Spatial Transcriptomics datasets as well as optimally leveraging integration with existing genomics datasets.

Applied AI Engineer

Cambridge, MA · On-site

$150 - $200/hr

Bachelor's in CS/ML/Computational Biology/Bioinformatics/Statistics/Engineering (or related) OR ... Single-cell RNA-seq/spatial transcriptomics/CRISPR assay (high-dimensional biological data)

... biomarker research, computational biology, statistical genetics, or related * 10+ years of ... spatial transcriptomics, methylation, imaging) * Credible as a thought partner with senior R&D ...

Bachelor's degree in Computer Science, Machine Learning, Computational Biology, Bioinformatics ... Familiarity with single-cell RNA-seq, spatial transcriptomics, CRISPR assay data, or other high ...

Showing results 21-40

Computational Spatial Transcriptomics information

See Peabody, MA salary details

$45

$60

$82

How much do computational spatial transcriptomics jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for computational spatial transcriptomics in Peabody, MA is $60.97, according to ZipRecruiter salary data. Most workers in this role earn between $52.02 and $81.63 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 job categories do people searching Computational Spatial Transcriptomics jobs in Peabody, MA look for?

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

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

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

Infographic showing various Computational Spatial Transcriptomics job openings in Peabody, MA as of August 2026, with employment types broken down into 2% Internship, 58% Full Time, 37% Part Time, 1% Temporary, and 2% Contract. Highlights an 58% Physical, 3% Hybrid, and 39% Remote job distribution, with an average salary of $126,817 per year, or $61 per hour.

Principal Scientist, Spatial Omics

Jj

Cambridge, MA • On-site

Full-time

Retirement, PTO

Re-posted 16 days ago


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Discovery & Pre-Clinical/Clinical Development

Job Sub Function:

Biological Research

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Spring House, Pennsylvania, United States of America

Job Description:

About Innovative Medicine:
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more athttps://www.jnj.com/innovative-medicine

We are searching for exceptional candidates for a Principal Scientist, Spatial Omics, role as part of Multiomics Discovery located in Cambridge, MA or Spring House, PA.

Purpose:
The ideal candidate will lead the development, validation, and deployment of cutting-edge spatial and molecular profiling capabilities to advance therapeutic discovery across neuroscience, oncology, and immunology, with deep expertise in at least one of these therapeutic areas preferred. This Principal Scientist role combines strategic leadership with hands-on scientific execution and is responsible for designing, optimizing, and applying molecular, phenotypic, and spatial assays that generate robust, reproducible, and biologically meaningful data.

The Principal Scientist will drive end-to-end development of functional genomics and spatial biology workflows, including genetic perturbation libraries, massively parallel reporter assays (MPRAs), pooled screening approaches, and spatial genomics technologies. The successful candidate will bring deep expertise in genomic technologies and will develop custom experimental workflows that integrate perturbation library design, cellular engineering, spatial guide capture, and transcriptomic profiling. The role will also be responsible for establishing and scaling laboratory infrastructure, implementing new technologies, and providing technical leadership across multiple experimental platforms.

Additional responsibilities include building data-generation pipelines, troubleshooting complex studies, and managing CROs and external technology partners to accelerate capability development and technology adoption. The position will provide opportunities to validate discoveries in relevant in vitro and ex vivo disease models and to collaborate closely with computational scientists to translate experimental findings into actionable biological insights.

Ideal candidates bring extensive experience in functional genomics, complex genetic screening, and spatial biology, preferably within a disease-focused research setting. They possess strong experimental design and assay development skills and have demonstrated success deploying novel genomic technologies across diverse cell and tissue systems. Candidates should have sufficient computational literacy to understand experimental data flows and interface effectively with bioinformatics and data science teams. Experience with spatial transcriptomics, genetic library design, massively parallel reporter assays, CRISPR-based perturbation approaches, pooled screening technologies, and cell engineering is highly desirable.

You will be responsible for:

  • Leading the development, optimization, andvalidation of spatial genomics and molecular profiling assaysto support neuroscience, oncology, and immunology programs.
  • Designing and executing experimental workflows involvingtissue processing, immunohistochemistry, in situ hybridization, microscopy, highresolution slide imaging and sequencing. Experience with Bruker CosMx and 10x Genomics Visium is highly preferred and will be required for this role.
  • Establishing and refiningnew functional genomics and massively parallel cell assays, including troubleshooting, workflow development, and technical feasibility assessments.
  • Building and scaling laboratory infrastructure, includinglab setup, instrumentation planning, and operational readiness.
  • ManagingCROs and external partners, ensuring highquality data generation, timeline alignment, and technical deliverables.
  • Collaborating closely with therapeutic area teams to translate multiomics and spatial readouts intoactionable biological insights.
  • Contributing to data workflows by supporting early-stagedata mapping, QC frameworks, and analytical handoffsto computational teams.

Qualifications

  • Education:
    • PhD in Genetics, Genomics, Molecular Biology, Molecular Pathology, Systems biology, Human biology or a related discipline is required.
    • Post-doctoral fellowship in a related field is required. Alternatively, industry experience with a proven track-record of delivering completed complex projects will be considered.

Required:

  • A minimum of 6 years of biotech or pharmaceutical industry experience is required. Academic staff scientist experience in deeply technical, matrixed, project facing roles will be considered.
  • Strong track record of high-impact scientific deliverables as evidenced by publications, presentations, and recognition within the scientific community.
  • Deep, technical spatial omics expertise is required, including understanding of end-to-end workflows, methods limitations, and mitigation strategies.
  • Excellent written communication, verbal communication, and oral presentation skills are required.
  • Experience with Multiomic Datasets is required.
  • Demonstrated ability to work across disciplines and functional areas is required.
  • Ability to apply novel approaches to address complex biology questions, as evidenced through strong peer-reviewed publications is required

Preferred:

  • Proficiency in programming languages such as R or Python is preferred.
  • In vitro cell culture and genomics library design experience is preferred.
  • Experience as a problem solver, and team collaborator able to facilitate understanding between biologists and data scientists is preferred.
  • Ability to manage multiple projects and meet deadlines is preferred.
  • Experience working with and/or guiding external collaborators in industry or academia is preferred

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or contact AskGS to be directed to your accommodation resource.

Required Skills:

Preferred Skills:

The anticipated base pay range for this position is :

$117,000.00 - $201,250.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits