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Spatial Transcriptomics Jobs in Houston, TX (NOW HIRING)

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Spatial Transcriptomics information

See Houston, TX salary details

$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 cities near Houston, TX are hiring for Spatial Transcriptomics jobs? Cities near Houston, TX with the most Spatial Transcriptomics job openings:
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.
Postdoctoral Fellow - Bioinformatics & Computational Biology

Postdoctoral Fellow - Bioinformatics & Computational Biology

MD Anderson Cancer Center

Houston, TX • On-site

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 12 days ago


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 full-time postdoctoral fellow position is available in Dr. Ye Zheng's lab at the Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center. We are seeking a highly motivated and dedicated postdoctoral researcher to join our dynamic, hybrid, and highly collaborative lab. This computational postdoctoral fellow candidate is expected to leverage single-cell/bulk-cell multi-omics, spatial omics, and pathological imaging data to reveal the cancer-specific mechanisms underlying the differential efficacies and toxicities of treatments across patients. This position offers an exciting opportunity to contribute to pioneering biological, clinically important and methodologically challenging problems by innovating cutting-edge statistical models, computational methods and AI agent skills. This position provides extensive training in grant writing, with a focus on prestigious early career development grants such as the K99 and Damon Runyon awards.
Dr. Zheng's lab works on problems at the interface of statistical, computational and biomedical sciences. The lab has developed methods to decipher gene cis-regulatory mechanisms from transcriptomics, epigenomics, proteomics and three-dimensional (3D) chromatin interaction perspectives.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
The postdoctoral fellow will achieve the following learning goals: (1) develop rigorous and reproducible statistical and machine learning methods for integrating multi-modality cancer datasets, with strong benchmarking and uncertainty awareness, and deliver these methods as well documented computational tools; (2) build AI pathology models that convert tissue morphology into quantitative features to support downstream molecular interpretation, including deconvolution and harmonization approaches for robust comparison across patients, cohorts, and tissue types; (3) create agentic AI workflows that automate analysis from data ingestion and quality control to interpretation and report generation, with emphasis on transparency, auditability, and scalability on high performance computing systems; (4) conduct integrative modeling of 3D genome organization and cross platform cell surface protein measurements to improve gene regulation insight and cell type and state characterization; (5) develop professional skills through structured mentorship in manuscript writing, scientific communication, and career development applications, including K99 R00 and Damon Runyon.
ELIGIBILITY REQUIREMENTS
Candidates with a Ph.D. in Computer Science, Statistics, Biostatistics, Bioinformatics, Computational Biology, Engineering, Data Science, or a related field are encouraged to apply.
1. Solid training in statistics and mathematics:
Past course or research training in statistics, including but not limited to mathematical statistics, statistical inference, and linear regression.
2. Strong computational skills:
• Proficient in developing computational tools and modern AI agent-related workflows.
• Proficient in programming languages R, Python, and Shell, has extensive experience in using high-performance computing environments on Linux servers, and knows how to submit batch-run jobs.
• Experienced in processing and analyzing bulk/single-cell genomic data, spatial omics data, or image data.
• Ability to conduct highly organized and reproducible research.
3. Genomics knowledge:
Have experience working on genetic or genomic data. Can interpret the biological findings.
4. Strong communication, writing, and collaboration ability.
5. First, co-first, corresponding, or co-corresponding publications and reprints under review on computational and/or statistical methodology development are required to demonstrate academic writing ability.
ADDITIONAL APPLICATION INFORMATION
Lab website and potential research project descriptions: https://compbiowizard.github.io./
To apply, please email the following to Dr. Ye Zheng at yzheng8@mdanderson.org.
(1) a cover letter describing past contributions to the field, future research plan, career development plan, scientific motivation and interests that align with Dr. Zheng's lab,
(2) a curriculum vitae that includes publications and GitHub links to past project codes or developed software
(3) emails and phone numbers of a list of three references
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000 . depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits , including medical, dental, paid time off , retirement , tuition benefits, educational opportunities, and individual and team recognition
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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