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Physics Informed Machine Learning Jobs in Cypress, 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 ...

New

SLB

FWI & AI Scientist

Houston, TX · On-site

... in physics-informed machine learning, learned solvers, or neural surrogate models. Proven success applying deep learning to physics-based modeling and simulation Experience deploying ML models at ...

Weatherford

Data Scientist / Wireline

Houston, TX · On-site

... machine learning models and statistical algorithms * Automate data workflows and analysis using modern programming tools * Modeling & Technical Contributions * Build predictive and physics-informed ...

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

As of Sep 3, 2026, the average hourly pay for physics informed machine learning in Cypress, TX is $17.28, according to ZipRecruiter salary data. Most workers in this role earn between $10.77 and $21.97 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

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 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.

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 popular job titles related to Physics Informed Machine Learning jobs in Cypress, TX?

For Physics Informed Machine Learning jobs in Cypress, TX, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Cypress, TX look for?

The top searched job categories for Physics Informed Machine Learning jobs in Cypress, TX are:

What cities near Cypress, TX are hiring for Physics Informed Machine Learning jobs?

Cities near Cypress, TX with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Cypress, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $35,945 per year, or $17.3 per hour.

Postdoctoral Associate - Earth Environmental Planetary Sciences

Rice University

Houston, TX • On-site

$65K/yr

Full-time

Posted 14 days ago

Rice University rating

8.2

Company rating: 8.2 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

150th of 628 rated colleges and universities

Job description


Position Summary
Dr. Ian McBrearty's lab in the Department of Earth, Environmental and Planetary Sciences is looking to hire a Postdoctoral Research Associate in the field of Machine Learning & Geophysics.
The McBrearty Lab sits at the intersection of machine learning and physics, focusing on developing data-driven techniques for earthquake monitoring, processing data from large seismic networks, and developing neural-surrogate emulations of PDEs governing tectonic and volcanic processes.
The ideal candidate will hold a Ph.D. in a quantitative field with strong Python and deep learning skills to build data-driven tools for earthquake detection and geophysical forecasting. They will be responsible for developing graph neural networks (GNNs), advancing PDE emulation methods, publishing high-impact research, and utilizing high-performance computing resources. Review of applications begins September 1, 2026, and will continue until the position is filled. Informal inquiries can be sent to Dr. Ian McBrearty at im76@rice.edu.
Workplace Requirements:
On campus position: This position is exclusively on-site, necessitating all duties to be performed in-person in Houston, Texas. Per Rice policy 440, work arrangements may be subject to change.
*Exempt (salaried) positions under FLSA are not eligible for overtime.
This position is funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.
Proposed Salary: $65,000
Essential Functions
  • Develops and deploys machine learning models (specifically graph neural networks) to process large, spatially irregular seismic datasets and advance neural-surrogate emulations of PDEs governing geophysical processes
  • Documents, analyzes, and maintains research data
  • Publishes and presents research findings
  • Supports project management and collaboration across institutions or disciplines
  • Performs all other duties as assigned

Required Qualifications and Skills
  • Ph.D. in Geophysics, Computer Science, Data Science, Applied Mathematics, or a related quantitative field
  • Strong Python programming skills and practical experience with deep learning frameworks (e.g., PyTorch, TensorFlow) for scientific data analysis
  • Excellent verbal and written communication skills, as well as oral presentation skills
  • Organization and time management skills
  • Knowledge of modern research methods, data collection, and analyses
  • Ability to write scholarly papers based on ongoing research in order to submit them to journals for publication
  • Able to work in a collaborative environment
  • Able to work independently and professionally with minimal supervision and direction

Preferred Qualifications
  • Experience with Graph Neural Networks (GNNs) or physics-informed machine learning (PINNs).
  • Background in seismological software packages (e.g., ObsPy) and large-scale, high-performance computing (HPC) data processing.

Rice University HR | Benefits: https://knowledgecafe.rice.edu/benefits
Rice Mission and Values: Mission and Values | Rice University
Rice University is committed to ensuring Equal Employment Opportunity and welcoming the fullness of diversity into our candidate pools. Rice considers qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability, or protected veteran status. Rice also provides reasonable accommodations to qualified persons with disabilities. If an applicant requires a reasonable accommodation for any part of the application or hiring process, please get in touch with Rice University's Human Resources Office via email at facstaffada@rice.edu for support.
If you have any additional questions, please email us at jobs@rice.edu . Thank you for your interest in employment with Rice University

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