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Computational Modeling Jobs in Houston, TX (NOW HIRING)

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How much do computational modeling jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for computational modeling in Houston, TX is $52.45, according to ZipRecruiter salary data. Most workers in this role earn between $44.76 and $70.24 per hour, depending on experience, location, and employer.

What is computational modeling?

A Computational Modeling job involves developing and using mathematical models, simulations, and algorithms to analyze complex systems across various fields, such as engineering, physics, biology, and finance. Professionals in this role apply computational techniques to study real-world phenomena, predict outcomes, and optimize processes. They often work with programming languages, statistical methods, and high-performance computing to create accurate and efficient models.

What are the key skills and qualifications needed to thrive in computational modeling?

To thrive in computational modeling, a strong background in mathematics, computer science, and domain-specific knowledge (such as engineering, physics, or biology) is essential, often supported by at least a bachelor's or master's degree in a related field. Familiarity with programming languages like Python, MATLAB, or R, as well as experience with simulation software and data analysis tools, is typically required. Strong problem-solving, analytical thinking, and effective communication skills set outstanding candidates apart. These abilities enable professionals to build accurate models, collaborate successfully with interdisciplinary teams, and translate complex results into actionable insights.

What does a computational modeler do?

A typical day for a computational modeling professional often involves developing and refining mathematical or computer-based models, running simulations, and analyzing large datasets to draw meaningful conclusions. You’ll collaborate closely with domain experts, engineers, and researchers to ensure models accurately reflect real-world processes. The role may also involve presenting findings to stakeholders, troubleshooting code or software issues, and keeping up with new modeling techniques and industry advancements. This dynamic environment requires balancing independent problem-solving with teamwork and communication.

What are the most commonly searched types of Computational Modeling jobs in Houston, TX? The most popular types of Computational Modeling jobs in Houston, TX are:
What are popular job titles related to Computational Modeling jobs in Houston, TX? For Computational Modeling jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Computational Modeling jobs in Houston, TX look for? The top searched job categories for Computational Modeling jobs in Houston, TX are:
What cities near Houston, TX are hiring for Computational Modeling jobs? Cities near Houston, TX with the most Computational Modeling job openings:
Infographic showing various Computational Modeling job openings in Houston, TX as of August 2026, with employment types broken down into 66% Full Time, 17% Part Time, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $109,105 per year, or $52.5 per hour.

Postdoctoral Fellow - Bioinformatics & Computational Biology

MD Anderson Cancer Center

Houston, TX • On-site, Remote

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

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 170 frontline employees who took The Breakroom Quiz

24th of 887 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.

  • 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.

  • 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.

  • Genomics knowledge:

Have experience working on genetic or genomic data. Can interpret the biological findings.

  • Strong communication, writing, and collaboration ability.
  • 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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