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Spatial Transcriptomics Jobs in Nebraska (NOW HIRING)

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Spatial Transcriptomics information

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?

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 are popular job titles related to Spatial Transcriptomics jobs in Nebraska?

For Spatial Transcriptomics jobs in Nebraska, the most frequently searched job titles are:

What job categories do people searching Spatial Transcriptomics jobs in Nebraska look for?

The top searched job categories for Spatial Transcriptomics jobs in Nebraska are:

Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in Nebraska as of August 2026, with employment types broken down into 74% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution.

Postdoctoral Research Associate

University of Nebraska Medical Center

Omaha, NE • On-site

Full-time

Re-posted 7 days ago

University Of Nebraska Medical Center rating

8.5

Company rating: 8.5 out of 10

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Job description

GENERAL REQUISITION INFORMATION
EEO Statement:
UNMC is an Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals with disabilities.
Location Omaha, NE Requisition Number: 2026 - 264 Department Genetics Cell Biology & Anatomy 50000507 Business Unit(College/Institute) College of Medicine FTE:
100
Reg-Temp Full-Time Regular Work Schedule 8:00 am - 5:00 pm Requisition Category Research - Academic Requisition Title Postdoctoral Research Associate Job Title/Academic Rank Postdoctoral Research Associate Additional Requisition Title Appointment Type A1 - REG OTHER ACAD SAL Salary Range Salary Commensurate with Experience Job/EEO Category Professional Non-Faculty (Includes Other Academic) Job Requisition Begin Date 06/25/2026
Position Qualification
Position Summary
Developing and/or applying artificial intelligence, machine learning and/or data science-based methods to address cutting-edge topics, including but not limited to, large language models and foundation models, single cell analysis, spatial transcriptomics, multi-omics analysis, cancer research, intelligent healthcare, and precision medicine.
Required Qualifications
The prospective postdocs should have a PhD degree in a related field, and have research experience in artificial intelligence, machine learning, bioinformatics, and computational biology. A strong programming capability is necessary.
Supplemental Qualifications
Preferences will be given to those who have research experience in large language models (LLMs)/foundation models (FMs), single-cell analysis, multi-omics analysis, spatial transcriptomics, cancer research, intelligent healthcare, or precision medicine.

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