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Computational Spatial Transcriptomics Jobs in Peabody, MA

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

... 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 ...

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Computational Spatial Transcriptomics information

See Peabody, MA salary details

$45

$60

$82

How much do computational spatial transcriptomics jobs pay per hour?

As of Aug 6, 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 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.
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 Computational Scientist - Discovery Biology N & I (Billerica MA)

The businesses of Merck KGaA, Darmstadt, Germany

Billerica, MA • On-site

Full-time

Medical, Retirement, PTO

Re-posted 7 hours ago


Job description

Work Your Magic with us!Start your next chapter and join EMD Serono.

Ready to explore, break barriers, and discover more? We know you've got big plans - so do we! Our colleagues across the globe love innovating with science and technology to enrich people's lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.

United As One for Patients, our purpose in Healthcare is to help create, improve and prolong lives. We develop medicines, intelligent devices and innovative technologies in therapeutic areas such as Oncology, Neurology and Fertility. Our teams work together across 6 continents with passion and relentless curiosity in order to help patients at every stage of life. Joining our Healthcare team is becoming part of a diverse, inclusive and flexible working culture, presenting great opportunities for personal development and career advancement across the globe.

This role does not offer sponsorship for work authorization. External applicants must be eligible to work in the US.


Your Role:

We are seeking an experienced computational biologist to drive translational target discovery and disease understanding in neuroscience and immunology, with a strong focus on functional genomics and human disease biology. This role will connect human genetics and patient-derived multi-omics data with experimental model systems and predictive disease modeling to support target identification, validation, and prioritization across the discovery pipeline.

As aPrincipal Scientist, Computational Biology - Functional Genomicswithin the Research Unit Neuroscience & Immunology (N&I), you will work at the interface of human genetics, computational biology, functional genomics, and translation, in close collaboration with bench scientists, disease area biologists, computational genetics colleagues, and cross-functional drug discovery teams. You will interpret genetic findings in biological context, generate mechanistic hypotheses, prioritize targets, and help guide the design and interpretation of perturbation-based experiments in disease-relevant systems.

A central part of the role is to help connecthuman disease biology to experimental validation and back again. You will translate human genetics and patient-derived multi-omics into testable functional hypotheses, help identify relevant preclinical model systems, and integrate perturbation and omics data from those models back with human datasets to assess translational relevance, refine disease mechanisms, and strengthen confidence in downstream clinical success.

You will integrate diverse data types - including human genetics, transcriptomics, proteomics, imaging, perturbation datasets, and single-cell or spatial omics where relevant - to uncover disease mechanisms and build scalable computational approaches for target validation and prioritization. You will contribute to predictive models of disease biology and perturbation response using systems biology, network analysis, and AI-enabled methods, with applications in disease modeling, patient stratification, disease endotyping, and therapeutic hypothesis prioritization. In partnership with cross-functional teams, you will also help integrate evidence on translatability, safety and toxicity risk, druggability, and modality considerations to support portfolio decisions.

Who You Are

Minimum Qualifications:

  • PhD in Computational Biology, Bioinformatics, Systems Biology, Biophysics, Data Science, or a related quantitative discipline, or in Biology, Medicine, Neuroscience, Immunology, or a related life science field with substantial specialization in computational biology
  • Significant postdoctoral and/or industry experience, including relevant experience inpharma or biotech drug discovery

Preferred Qualifications:

  • Strong experience in computational biology appliedto target discovery, functional genomics, translational biology, or disease modeling
  • Experience interpretinghuman genetics and patient-derived multi-omicsdata to generate mechanistic hypotheses and support target identification or validation
  • Experience integrating complex datasets, including combinations oftranscriptomics, proteomics, perturbation data, imaging, genetics, and single-cell or spatial omics
  • Good understanding of how to connecthuman disease biology with preclinical model systems, including assessing translational relevance and supporting model selection or data interpretation
  • Experience withperturbation biologyor functional genomics data, such as CRISPR/RNAi screening, Perturb-seq, Cell Painting, or related approaches
  • Strong programming skills inPython and/orR, with experience building reproducible analytical workflows
  • Familiarity withsystems biology, network analysis, gene regulatory networks, knowledge graphs, machine learning, or AI-enabled approachesfor biological data integration and predictive modeling
  • Understanding ofdrug discovery and development, including target prioritization, translatability, safety and toxicity considerations, druggability, and modality-related questions
  • Experience leading scientific projects and collaborating effectively across multidisciplinary and cross-functional teams
  • Analytical, hypothesis-driven, and creative, with the ability to connect complex data to clear biological and strategic decisions
  • Strong communication skills in English, including the ability to explain complex computational concepts to diverse scientific audiences

What we are looking for

We are looking for an experienced scientist who combinesdeep computational expertise, strong biological intuition, translational thinking, and pharma drug discovery experience. You are excited by the opportunity to connect human disease biology with experimental validation, integrate diverse data types into mechanistic insight, and help shape data-driven decisions in target discovery and translational research.

You are:

  • scientifically rigorous and hypothesis-driven
  • strategic, creative, and impact-oriented
  • collaborative and effective in cross-functional environments
  • comfortable working across discovery, functional genomics, and translation
  • motivated to connect complex data to clear biological and portfolio decisions

Location: On-site Billerica MA

Pay Range for this position: $140,200 - $210,200

The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other perquisites. For more information click here.


What we offer: We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress!

Apply now and become a part of a team that is dedicated to Sparking Discovery and Elevating Humanity!

Employment Type: FULL_TIME