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Physics Informed Machine Learning Jobs in Houston, TX

ExxonMobil

Computational Scientist

Spring, TX · On-site

Experience in surrogate modeling approaches (e.g., deep learning, machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational ...

ExxonMobil

Computational Scientist

Spring, TX · On-site

Experience in surrogate modeling approaches (e.g., deep learning, machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational ...

ExxonMobil

Computational Scientist

Spring, TX

Experience in surrogate modeling approaches (e.g., deep learning, machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational ...

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

Bachelor's degree in computer science, mathematics, physics, engineering or related field required ... machine learning methods and algorithms * Strong Python or R programming skills required

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

Bachelor's degree in computer science, mathematics, physics, engineering or related field required ... machine learning methods and algorithms * Strong Python or R programming skills required

NobleAI

Senior Applied AI/ML Scientist

Houston, TX · On-site +1

By combining physics and chemistry expertise with advanced machine learning, our platform improves ... Familiarity with physics-informed ML, geological/reservoir modeling, and/or production forecasting ...

NobleAI

Senior Applied AI/ML Scientist

Houston, TX · Remote

By combining physics and chemistry expertise with advanced machine learning, our platform improves ... Familiarity with physics-informed ML, geological/reservoir modeling, and/or production forecasting ...

Talentry, LLC

Be Seen First

Machine Learning Guru (Autonomous Navigation)**

Houston, TX · Remote

$200K - $300K/yr

D. or Master's) in computer science, computer engineering, mathematics, physics, or related field. * In-depth knowledge and experience in machine learning and/or computer vision, employing bleeding ...

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How much do physics informed machine learning jobs pay per hour?

As of May 29, 2026, the average hourly pay for physics informed machine learning in Houston, TX is $19.16, according to ZipRecruiter salary data. Most workers in this role earn between $11.92 and $24.33 per hour, depending on experience, location, and employer.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.
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Computational Scientist

Computational Scientist

ExxonMobil

Spring, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 22 days ago

ExxonMobil rating

6.0

Company rating: 6.0 out of 10

Based on 219 frontline employees who took The Breakroom Quiz

57th of 74 rated oil and gas companies

Job description

About us
At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world's largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.
The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.
We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society's evolving needs. Learn more about our What and our Why and how we canwork together.
About Houston
ExxonMobil's state-of-the-art campus north of Houston serves as home to its Upstream, Product Solutions and Low Carbon Solutions businesses and their associated service groups. The facility opened in 2014 and accommodates more than 10,000 employees and visitors.
By bringing many global functional groups together, the campus provides employees with the tools and capabilities needed today, and in the future, to achieve business objectives and accelerate the discovery of new resources, technologies and products. It was designed to foster improved collaboration, creativity and innovation and enhance the company's ability to attract, develop and retain the top talent in the industry.
The campus is located in Spring, Texas, on 385 wooded acres immediately to the west of Interstate Highway 45 (I-45), at the intersection of I-45 and the Hardy Toll Road, approximately 25 miles from the cultural vibrancy of downtown Houston.
The campus was constructed to the highest standards of energy efficiency and environmental stewardship. Its design incorporates extensive research into best practices in building and workplace design through extensive benchmarking of the world's top academic, research, and corporate facilities.
Learn more about what we do in Houston here
What role you will play in our team
We are seeking a highly skilled and motivated Computational Scientist to join our team. This role involves developing and analyzing both physics-based and data-driven computational models to tackle a range of problems in the oil and gas industry.
What you will do
  • Work collaboratively across global, cross-disciplinary teams, and with third parties (academia, industry) to assess, accelerate pace of computational science technology development and deployment.
  • Frame computational challenge from business needs, develop solutions that strike a balance between accuracy and runtimes, develop solutions that merge physics and data incorporating uncertainty, develop novel approaches to constrain predictive models with field data.

Skills & Qualifications
  • PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field.
  • Experience in developing, applying, and analyzing physics-based models and developing related algorithms.
  • Strong background in multiscale and/or multiphysics mathematical modeling, scientific computing, and numerical analysis.
  • Hands-on experience with deep learning, including familiarity with a range of architectures (e.g., autoencoder, transformer, diffusion model, GAN) and their application to industrial, engineering, or scientific problems.
  • Experience in surrogate modeling approaches (e.g., deep learning, machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational cost in decision-making processes (e.g., optimization, inverse problems, data assimilation) while maintaining fit-for-purpose accuracy.
  • Experience in formulating and solving convex and PDE constrained optimization problems.
  • Strong proficiency in programming/scripting languages like Python or C++/C#.
  • Proficiency in ML frameworks (PyTorch, TensorFlow, scikit-learn); experience with Databricks/Spark is a plus.
  • Experience with software engineering best practices including software testing, agile development, version control, and DevOps.
  • Experience working in Linux and High-Performance Computing environment is desirable but not required.
  • Prior experience in the upstream oil and gas industry is an advantage.
  • Strong communication skills and ability to work effectively in interdisciplinary teams to translate complex computational models into actionable insights.

Your benefits
An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life.
We offer you:
  • Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life.
  • Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match.
  • Workplace Flexibility: We have several programs such as "Flex your Day", providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work.
  • Comprehensive medical, dental, and vision plans.
  • Culture of Health: Programs and resources to support your wellbeing.
  • Employee Health Advisory Program: Provides confidential professional counseling for you and your family, including tools and resources promoting mental health and resiliency at no additional cost to you.
  • Disability Plan: Income replacement for when you cannot work due to illness or injury occurring on or off the job. Enrollment is automatic and at no cost to you.

More information on our Company's benefits can be found at www.exxonmobilfamily.com.
Please note benefits may be changed from time to time without notice, subject to applicable law.
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Alternate Location:
Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.
Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

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