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Computational Science Jobs in Texas (NOW HIRING)

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site

Masters in geoscience, lunar science, planetary science, image science, GIS, remote sensing, computational science or relevant science fields with applicable experience * 5+ years of work experience

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site

Masters in geoscience, lunar science, planetary science, image science, GIS, remote sensing, computational science or relevant science fields with applicable experience * 5+ years of work experience

The Jacobs Brand

GIS Developer

Houston, TX · On-site +1

Masters in geoscience, lunar science, planetary science, image science, GIS, remote sensing, computational science or relevant science fields with applicable experience * 5 years of work experience

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site +1

Masters in geoscience, lunar science, planetary science, image science, GIS, remote sensing, computational science or relevant science fields with applicable experience * 5+ years of work experience

Pae

GIS Developer

Houston, TX · On-site +1

Mastersin geoscience, lunar science, planetary science, image science, GIS, remote sensing, computational science or relevant science fields with applicable experience * 5+ years of work experience

Roku

Senior Computational Linguist

Austin, TX

About the Role We are looking for a top-notch Sr. Computational Linguist who is passionate about ... D. degree in Linguistics, Computer Science, or related field * Proficiency in at least one non ...

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Computational Science information

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$52.6K

$77.4K

$91.3K

How much do computational science jobs pay per year?

As of Jun 27, 2026, the average yearly pay for computational science in Texas is $77,429.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,200.00 and $87,100.00 per year, depending on experience, location, and employer.

What are some common challenges faced by computational scientists when working on interdisciplinary projects?

Computational scientists often collaborate with experts from fields like biology, physics, or engineering, which can present challenges in bridging gaps in domain-specific knowledge and communication styles. Adapting computational models to fit the unique requirements of different disciplines, while ensuring accuracy and efficiency, is a frequent hurdle. Additionally, managing large datasets and integrating diverse computational tools requires strong technical and organizational skills. Open communication and a willingness to learn from colleagues are key to overcoming these challenges and achieving successful project outcomes.

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

To thrive as a Computational Scientist, you need a strong background in mathematics, programming (such as Python, C++, or MATLAB), and domain-specific scientific knowledge, often supported by an advanced degree in a relevant field. Familiarity with high-performance computing (HPC) systems, parallel processing frameworks, and scientific data analysis tools is typically required. Excellent problem-solving skills, collaboration, and effective communication set top candidates apart in interdisciplinary research environments. These skills and qualities are crucial for driving innovative scientific discovery and translating complex data into actionable insights.

What is the difference between Computational Science vs Data Scientist?

AspectComputational ScienceData Scientist
Required CredentialsDegree in science, engineering, or computational fields; often requires advanced degreesDegree in statistics, computer science, or related fields; often requires knowledge of programming and analytics
Work EnvironmentResearch labs, universities, industry R&D departmentsTech companies, finance, healthcare, consulting firms
Industry UsageScientific research, simulation, modelingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

Computational Science focuses on developing models and simulations to solve scientific and engineering problems, often requiring advanced degrees and research environments. Data Scientists analyze large datasets to extract insights and support decision-making, typically working in business or tech sectors. While both roles involve programming and data handling, their primary goals and work settings differ significantly.

What can you do with a computational science degree?

A computational science degree prepares individuals for roles such as computational scientist, data analyst, simulation engineer, or research scientist. Graduates often work in industries like healthcare, finance, aerospace, and academia, utilizing skills in programming, modeling, and data analysis to solve complex problems. Knowledge of tools like Python, MATLAB, or high-performance computing environments is also valuable.

What is computational science?

Computational science is an interdisciplinary field that uses advanced computing capabilities to understand and solve complex problems. It combines elements of mathematics, computer science, and domain-specific knowledge to create simulations, analyze data, and model physical, biological, or social systems. Computational scientists develop algorithms and use high-performance computing to tackle problems that are difficult or impossible to solve analytically. This field is essential in areas such as climate modeling, drug discovery, engineering, and physics.

What does a computational scientist do?

A computational scientist develops and applies computer models, algorithms, and simulations to analyze complex scientific problems across fields like physics, biology, and engineering. They often use programming languages, high-performance computing, and data analysis tools to interpret large datasets and support research decisions.

What is computational science salary?

Computational science professionals typically earn a median salary ranging from $70,000 to $120,000 annually, depending on experience, education, and location. Advanced skills in programming, data analysis, and familiarity with scientific software can influence earning potential.

Is computational science a good degree?

Computational science is a valuable degree for careers in research, data analysis, and simulation-based roles across industries such as engineering, finance, and technology. It typically requires strong skills in programming, mathematics, and problem-solving, and can lead to well-paying jobs with opportunities for advancement. The degree prepares students for interdisciplinary work involving scientific computing tools and methods.
What are popular job titles related to Computational Science jobs in Texas? For Computational Science jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Computational Science jobs in Texas look for? The top searched job categories for Computational Science jobs in Texas are:
What cities in Texas are hiring for Computational Science jobs? Cities in Texas with the most Computational Science job openings:
Computational Science jobs near you
Infographic showing various Computational Science job openings in Texas as of June 2026, with employment types broken down into 38% Full Time, 56% Part Time, 4% Contract, and 2% Nights. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $77,429 per year, or $37.2 per hour.
Assistant Professor - Advanced Imaging (MRI Technology) [Req#: 891221, Position#: 129094]

Assistant Professor - Advanced Imaging (MRI Technology) [Req#: 891221, Position#: 129094]

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Posted 15 days ago

UT Southwestern rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

105th of 877 rated healthcare providers

Job description

Description
The Advanced Imaging Research Center (AIRC) at UT Southwestern Medical Center in Dallas, Texas, invites applications for a tenure-track Assistant Professor position in the field of MRI Technology Development.
Potential topics include but are not limited to:
  • Electromagnetic field modeling
  • Radiofrequency coil design
  • Ultimate intrinsic SNR calculations
  • Electrical Property mapping
  • AI driven MRI reconstruction
  • AI driven MRI sequence optimization
  • AI driven MRI analysis pipeline development

Qualifications
Applicants for this position should have a strong scientific record of accomplishment in MRI Technology Development. Experience in supervising graduate students and/or postdoctoral researchers is preferred. Applicants should have a Ph.D. degree in electrical engineering, physics, computational science, biomedical engineering or applied mathematics.
Application Instructions
Applications should include a letter of interest and a curriculum vitae.

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