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Spatial Transcriptomics Jobs in Texas (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, 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 cities in Texas are hiring for Spatial Transcriptomics jobs? Cities in Texas with the most Spatial Transcriptomics job openings:
Infographic showing various Spatial Transcriptomics job openings in Texas as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Senior Data Scientist Immunotherapy Platform

Senior Data Scientist Immunotherapy Platform

MD Anderson

Houston, TX • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 169 frontline employees who took The Breakroom Quiz

27th of 884 rated healthcare providers


Job description

UT MD Anderson is seeking a Senior Data Scientist (Computational Biology) to support advanced translational research within the Immunotherapy Platform (IMT) at the James P. Allison Institute. The Senior Data Scientist (Computational Biology) will lead complex analyses of multi-modal cancer datasets, helping to uncover mechanisms of tumor-immune interactions and therapeutic response.

This role offers the opportunity to independently drive high-impact research projects from analytical design through biological interpretation and publication. UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. The Senior Data Scientist (Computational Biology) will play a central role in accelerating scientific discovery within IMT by collaborating with clinicians, immunologists, and researchers, contributing to publications and grant applications, and advancing computational approaches in cancer immunotherapy.

The ideal candidate will have computational experience. Experience with multi-modal omics data, single-cell and spatial transcriptomics. Experience in academic or healthcare environment.

Why Us. This role offers the opportunity to contribute directly to transformative cancer immunotherapy research at UT MD Anderson, working alongside leading scientists in a highly collaborative environment. The position supports professional growth through publication, grant involvement, and development of advanced computational expertise, while offering a balanced and supportive work environment.

Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance. Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options. Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.

Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs. Responsibilities Data Analysis Analyze high-dimensional biomedical datasets including single-cell RNA-seq, spatial transcriptomics (CosMx, Visium, CODEX), bulk RNA-seq, and clinical datasets Characterize tumor microenvironment, immune cell states, and cell-cell interactions Integrate multi-modal datasets including genomic, spatial, proteomic, and clinical data Develop reproducible and scalable analytical workflows Apply strong programming skills in Python and/or R to data processing and analysis Utilize public cancer datasets such as TCGA and GEO where appropriate Project Development Design and execute end-to-end computational analyses aligned with IMT research priorities Propose independent analytical strategies and hypotheses Collaborate with experimental and clinical teams to refine biological questions Develop reusable pipelines and analytical frameworks (e.g., GitHub) Contribute to cross-project standardization of analysis approaches Research Generate biologically meaningful insights from complex datasets Contribute to manuscripts with expectation of first or co-first authorship Support grant development through computational analysis and data interpretation Stay current with emerging computational biology methods and apply them to IMT datasets EDUCATION: Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Preferred: PhD Science, Engineering or related field

EXPERIENCE: Required: Five years experience in scientific software or industry programming with a concentration in scientific computing. With master's degree, three years experience. With PhD, one year experience.

Preferred: Genomic experience. Developing AI models. Ability to independently lead projects.

Experience single-cell RNA-seq and/or spatial transcriptomics. Experience in academic or healthcare environment. 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.

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 Additional Information Requisition ID: 180473 Employment Status: Full-Time Employee Status: Regular Work Week: Days Minimum Salary: US Dollar (USD) 123,000 Midpoint Salary: US Dollar (USD) 154,000 Maximum Salary : US Dollar (USD) 185,000 FLSA: exempt and not eligible for overtime pay Fund Type: Soft Work Location: Hybrid Onsite/Remote Pivotal Position: Yes Referral Bonus Available?: Yes Relocation Assistance Available?: Yes #LI-Hybrid Apply


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