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Physics Informed Machine Learning Jobs in New Mexico

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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.

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 popular job titles related to Physics Informed Machine Learning jobs in New Mexico? For Physics Informed Machine Learning jobs in New Mexico, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in New Mexico look for? The top searched job categories for Physics Informed Machine Learning jobs in New Mexico are:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in New Mexico as of June 2026, with employment types broken down into 6% Internship, and 94% Full Time. Highlights an 100% In-person job distribution.
Scientific Software Developer Paid Co-op/Internship

Scientific Software Developer Paid Co-op/Internship

Stellar Science

Albuquerque, NM • On-site

$18.75 - $24.50/hr

Internship

Posted 11 days ago

Job description

Selected Interns or Co-op students will support object-oriented C++ software development in the following domains: space domain awareness (SDA), image simulation, space systems modeling, laser source generation and effects modeling, high power microwave systems modeling and simulation, computer vision, image processing, artificial intelligence (AI), machine learning (ML), atmospheric modeling, computational electromagnetics (CEM), high performance computing (HPC), computer aided design (CAD) tools, meshing, thermal modeling, and more.
The main requirements are that candidates be top-notch, responsible, self-motivated, honest, able to work well independently or in small teams, and be able to rapidly learn new languages, tools, and techniques as needed to meet mission requirements.
Applicants who convey a passion for developing quality code, through listed projects, a github link, or other software development experiences, will be given preference.
This is a paid cooperative/internship learning experience.
Minimum Requirements:
  • Majoring in physics, math, electrical/mechanical/aerospace engineering, computer science, or any relevant scientific or engineering field
  • Ability to implement, understand, and maintain mathematical and scientific software libraries
  • Software development experience in C++
  • Must be available for full time employment within a year of completing this internship
  • U.S. citizen willing to undergo background investigation and perform some work at government or customer sites

Experience in any of the following is a plus:
  • Cross-platform software development on Linux and Windows
  • 3D graphics using OpenGL, Open Scene Graph, WebGL, Vulkan
  • User interface development with Qt, Java Swing, Typescript, React, MaterialUI
  • Supercomputing, CUDA, OpenMP, MPI, threads, GPU
  • Image processing, imagery analysis, computer vision, computer aided design (CAD), meshing
  • Aerospace vehicles, orbital mechanics, electromagnetics, space domain awareness
  • Artificial Intelligence, Machine Learning
  • Modeling and simulation
  • Directed energy (lasers, microwave), thermal analysis

A representative sample of your code will be requested early in the evaluation process, e.g. something you've written for work, a school project, or for fun. It should be long enough to demonstrate your programming and software engineering skills.
About Stellar Science: We are a growing Albuquerque-based computational science company seeking talented computer programmers to create and extend exciting scientific and engineering analysis applications. We maintain high standards in all our software development efforts, utilizing modern development practices including continuous integration, test-driven development, pair programming, and code reviews in order to develop high quality, maintainable, and reusable code. By employing a lightweight development process, we remain highly productive and responsive to changing customer needs.

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