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Computational Spatial Transcriptomics Jobs (NOW HIRING)

This position is engaged in the field of Spatial transcriptomics and bioinformatics. This position ... Bachelor's degree in Bioinformatics, Computational Biology, Biostatistics, Data Science or a ...

Perform high-quality computational analysis of next-generation sequencing (NGS) data, including short and long-read whole-genome, whole-exome, RNA-seq, and spatial transcriptomics datasets. * Develop ...

Bioinformatics Scientist

Bethesda, MD · On-site

$65K - $108K/yr

D. in Bioinformatics, Computational Biology, or a related discipline preferred. * Experience with Xenium and/or Visium spatial transcriptomics platforms is preferred. * Familiarity with adaptive ...

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Computational Spatial Transcriptomics information

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$54

$74

How much do computational spatial transcriptomics jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for computational spatial transcriptomics in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 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.
More about Computational Spatial Transcriptomics jobs
What cities are hiring for Computational Spatial Transcriptomics jobs? Cities with the most Computational Spatial Transcriptomics job openings:
What states have the most Computational Spatial Transcriptomics jobs? States with the most job openings for Computational Spatial Transcriptomics jobs include:
Infographic showing various Computational Spatial Transcriptomics job openings in the United States as of July 2026, with employment types broken down into 68% Full Time, 31% Part Time, and 1% Contract. Highlights an 65% Physical, 2% Hybrid, and 33% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Scientific Lead, Molecular Characterization

Eli Lilly and Company

New York, NY

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago


Eli Lilly and Company rating

8.8

Company rating: 8.8 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical


Job description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We're looking for people who are determined to make life better for people around the world.

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We're looking for people who are determined to make life better for people around the world.

Position Summary

The Scientific Lead position would be the principal architect for spatial biology and long-read genomics within the Molecular Characterization team in Discovery Technologies, responsible for developing, optimizing, and scaling these platforms in support of Oncology drug discovery at Lilly. The Molecular Characterization team sits at the intersection of genomics, proteomics, and emerging molecular technologies, providing cutting-edge platform capabilities across Lilly's discovery portfolio. The central mandate is invention: defining what next-generation spatial and long-read platforms can do, and building the infrastructure to realize their full potential within the group.

The successful candidate will possess deep, applied expertise in spatial transcriptomics (e.g., Visium HD, CosMx, Xenium), with working knowledge of long-read sequencing (PacBio/Nanopore) and demonstrated experience in the automation of complex NGS workflows. Of equal importance is an entrepreneurial scientific mindset, a genuine drive to evaluate and deploy emerging tools that have not yet been established as standard practice within the field. This is a hands-on role where direct experimentation and platform development are central to scientific impact, with growing opportunities to shape scientific direction and mentor junior team members as the platforms mature. This position requires close collaboration with Oncology project teams, automation specialists, histology, and discovery informatics to translate novel molecular insights into actionable biology.

Key Responsibilities

  • Design and lead the development of spatial transcriptomics and multi-modal spatial workflows, encompassing tissue optimization, library construction, and end-to-end data generation using platforms such as Visium HD, CosMx, and Xenium.

  • Drive the integration of spatial transcriptomics with complementary modalities, including spatial proteomics (e.g., CosMx protein panels, CODEX/PhenoCycler) and single-cell data, to generate comprehensive tissue-level molecular maps.

  • Establish and continuously improve tissue processing standards for diverse sample types relevant to Oncology (FFPE, fresh-frozen, bone marrow, cryosections), with a focus on maximizing data quality from challenging or low-input specimens.

  • Develop image analysis pipelines in collaboration with discovery informatics, including tissue segmentation, cell type deconvolution, and morphological co-registration using tools such as QuPath, HALO, or equivalent platforms.

  • Evaluate emerging spatial technologies on an ongoing basis and translate promising platforms into internal capabilities through systematic feasibility assessment and implementation planning.

  • Scale long-read sequencing workflows (PacBio and Oxford Nanopore) for applications including structural variant detection, isoform characterization, epigenetic sequencing (e.g., methylation, Fiber-seq), and custom targeted approaches.

  • Contribute to automation of NGS and spatial library preparation protocols in collaboration with automation and histology specialists.

  • Develop custom targeted panels and probe/index designs for the spatial platforms to address specific genomic and transcriptomic questions posed by Oncology project teams.

  • Establish protocol QC frameworks and performance benchmarks to ensure data integrity across all high-throughput molecular platforms.

  • Apply and adapt spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) to process, visualize, and interpret spatial transcriptomics datasets in close partnership with the discovery informatics team.

  • Work with bioinformaticians to design and evaluate computational workflows for long-read data, including isoform quantification, structural variant calling, and base modification detection.

  • Serve as the internal scientific authority on spatial and long-read sequencing platforms; advise Oncology project teams on platform selection, experimental design, and interpretation.

  • Provide mentorship and hands-on coaching to junior scientists; build a team culture grounded in technical rigor, creative problem-solving, and collaborative execution.

  • Establish and manage relationships with academic collaborators, technology vendors, and contract research organizations to stay at the leading edge of platform development.

  • Prepare and deliver scientific presentations, publications, and study reports to internal and external audiences.

  • Maintain up-to-date knowledge of the scientific landscape in spatial biology, long-read genomics, and multi-omics; proactively share emerging opportunities with the broader team.

Required Qualifications

  • PhD in molecular biology, genomics, genetics, or a closely related discipline, with 3+ years of hands-on research or platform development experience in an academic or industry setting.

Additional Preferred Qualifications

  • Deep hands-on expertise in spatial transcriptomics platforms (Visium HD, CosMx, Xenium, or equivalent), from tissue section preparation through library construction and QC.

  • Demonstrated experience with tissue optimization and sample handling for spatial applications across diverse and challenging sample types (FFPE, fresh-frozen, bone marrow, cryosections).

  • Familiarity with long-read sequencing platforms (Oxford Nanopore and/or PacBio); hands-on experience with library construction, QC, and data interpretation is a strong plus.

  • Proven experience automating NGS or spatial library preparation workflows using liquid handling platforms (e.g., Hamilton, Beckman Coulter, or equivalent).

  • Working knowledge of spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) and image analysis platforms (e.g., QuPath, HALO) for tissue-based data.

  • Proficiency scripting in Python and/or R to apply, adapt, and troubleshoot single-cell and spatial analysis tools (e.g., Scanpy/Squidpy, Seurat).

  • Demonstrated track record of building or deploying new molecular platforms or technologies, not solely operating established protocols.

  • Broad NGS experience including RNA-seq, WES, single-cell sequencing, and epigenetic profiling (ATAC-seq, bisulfite sequencing, or equivalent).

  • Excellent scientific communication skills; ability to convey complex results clearly to technical and non-technical stakeholders.

  • Demonstrated ability to work independently and as part of a cross-functional team in a fast-paced environment with evolving priorities.

  • Experience with multimodal spatial platforms integrating transcriptomics and proteomics (e.g., CosMx protein, CODEX/PhenoCycler).

  • Familiarity with long-read epigenetic methods such as Fiber-seq or direct methylation detection via Nanopore.

  • Experience developing novel targeted sequencing panels, including probe design and index optimization.

  • Knowledge of multi-omics platforms such as Nanostring, Quanterix, Luminex, or Fluidigm.

  • Experience processing and interpreting large-scale biological datasets; familiarity with Spotfire or similar data visualization tools.

  • Experience in GLP environments or regulated laboratory settings.

Work Environment and Physical Demands

This position is primarily laboratory-based. Travel requirements are less than 5%. The physical demands described are representative of those required to successfully perform the essential functions of this role. Reasonable accommodations may be made for individuals with disabilities.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.


Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women's Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is

$138,000 - $224,400

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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About Eli Lilly

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Eli Lilly, based in Indianapolis, IN, US, is one of the pioneers in the pharmaceutical industry with a rich history dating back to 1876. This global pharmaceutical company focuses on discovering, developing, manufacturing and selling pharmaceutical products in approximately 120 countries. The company's product categories include endocrinology, oncology, cardiovascular, neuroscience, and immunology. Having invested over $9 billion in research and development in the past decade, Eli Lilly is also committed to creating high-quality medicines that meet real needs. As a recipient of several awards and recognitions, Eli Lilly is known for its focus on life-saving research and drug development. Their mission is to make medicines that help people live longer, healthier, and more active lives.

Industry

Pharmaceutical product wholesalers

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

1876