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$46.8K

$194.3K

$382K

How much do spatial transcriptomics jobs pay per year?

As of Jun 4, 2026, the average yearly pay for spatial transcriptomics in Houston, TX is $194,306.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $382,000.00 per year, depending on experience, location, and employer.

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

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 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 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 popular job titles related to Spatial Transcriptomics jobs in Houston, TX? For Spatial Transcriptomics jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics jobs in Houston, TX look for? The top searched job categories for Spatial Transcriptomics jobs in Houston, TX are:
What cities near Houston, TX are hiring for Spatial Transcriptomics jobs? Cities near Houston, TX with the most Spatial Transcriptomics job openings:
Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in Houston, TX as of May 2026, with employment types broken down into 3% Internship, 69% Full Time, 11% Part Time, 3% Temporary, 11% Contract, and 3% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $194,306 per year, or $93.4 per hour.
Research Intern - Translational Molecular Pathology

Research Intern - Translational Molecular Pathology

MD Anderson Center

Houston, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

32nd of 865 rated healthcare providers

Job description

A research intern position is available in the department of Translational Molecular Pathology. We seek a research intern to develop, implement, and deploy innovative computational pipelines for multimodal pathology data repositories. The research intern will develop cutting edge artificial intelligence (AI) tools in multimodal pathology that spans digital pathology, spatial transcriptomics/proteomics, and language processing. The research intern will be closely mentored by Dr. Song. The research intern will also collaborate and consult with pathologists and clinicians to address key clinical challenges that will have an impact on our patients.
The University of Texas MD Anderson Cancer Center provides the ideal environment for developing, testing, and deploying AI technologies for improved early cancer diagnosis and accurate treatment selection. The Computational Pathology program is a key focus area of the IDSO and supports the IDSO's mission to drive high-impact discovery research by optimizing multidimensional data integration, analysis, and application.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Develop impact-driven AI technologies for pathology
-Develop and maintain computational methods with AI in multimodal pathology.
- Work with a highly interdisciplinary team to generate biologically meaningful results and work towards clinical translation of AI for oncology. - Keep current and evaluate state-of-the-art methods and tools, establish and help maintain computational infrastructure and analytic pipelines. - Present results in collaboration meetings, internal and external conferences.
ELIGIBILITY REQUIREMENTS
Applicant must hold a bachelor's or master's degree
Degree must have been obtained recently (within one year)
Applicant must have previous research experience
Applicants who hold a Ph.D. or equivalent doctoral degree (e.g., M.D., D.V.M., M.B.B.S.) are not eligible
Ideal candidates will have a minimum of a bachelor's degree in electrical engineering, Computer Science, Physics, Applied Mathematics, Biomedical Engineering, Statistics, Computational Biology, or related field, with extensive experience in scientific software development/analysis (specifically in Python, image processing and Deep Learning)
ADDITIONAL APPLICATION INFORMATION
Translational Molecular Pathology Department web site: https://www.mdanderson.org/research/departments-labs-institutes/departments-divisions/translational-molecular-pathology.html
Visit Dr. Song's website (https://andrewhsong.com) for more information.
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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