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Scientific Machine Learning Jobs in Bryan, TX (NOW HIRING)

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Python Tutor

College Station, TX · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

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Python Tutor

Bryan, TX · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Varsity Tutors

Linear Algebra Tutor

Bryan, TX · Remote

$18 - $40/hr

... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Varsity Tutors

Linear Algebra Tutor

College Station, TX · Remote

$18 - $40/hr

... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Bryan, TX

Scientific Machine Learning information

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$12

$29

$48

How much do scientific machine learning jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for scientific machine learning in Bryan, TX is $29.02, according to ZipRecruiter salary data. Most workers in this role earn between $17.74 and $37.02 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What job categories do people searching Scientific Machine Learning jobs in Bryan, TX look for?

The top searched job categories for Scientific Machine Learning jobs in Bryan, TX are:

What cities near Bryan, TX are hiring for Scientific Machine Learning jobs?

Cities near Bryan, TX with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you

Tenure-Track: Assistant Professor

Texas A&M University

College Station, TX • On-site

Full-time

Re-posted 2 days ago

Texas A&M University rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

237th of 630 rated colleges and universities

Job description

Description
The Department of Statistics and Data Science in the College of Arts & Sciences at Texas A&M University invites applications for two tenure-track Assistant Professor positions with anticipated start dates in August 2027. Both positions will be full-time, 9-month appointments.
The department encourages people from all areas of research to apply and is particularly interested in expertise in the broad areas of Biostatistics/Bioinformatics or Statistical AI/Machine Learning. Evidence of interdisciplinary research and focus on computational aspects is a plus. In addition to conducting outstanding research, the successful candidate will be expected to teach undergraduate and graduate courses, supervise graduate students, and provide service to the profession. Excellent computing facilities are available, and highly competitive startup funding and starting salaries are anticipated.
The Department of Statistics has a tradition of outstanding methodological, theoretical, computational, and interdisciplinary research. Current faculty members actively collaborate with colleagues within the department, throughout the university, and at many outside institutions.
Qualifications
A PhD/DSc degree in Statistics, Biostatistics, Computer Science, Engineering or related fields is required.
Application Instructions
Interested applicants must include a cover letter, current Curriculum Vitae (CV), a personal statement to include philosophy and plans for research, teaching and service, as applicable, and three (confidential) professional references.
To apply, please visit apply.interfolio.com/191883. All applications received by November 6, 2026, will receive full consideration. Applications will continue to be accepted until the position is filled. Please direct all inquiries to Dr. Samiran Sinha, Search Committee Chair at hiring@stat.tamu.edu.

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