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Physics Informed Machine Learning Jobs in Michigan

Freudenberg

Materials Informatics Scientist

Howell, MI · On-site

Leads activities in generative AI and physics-informed machine learning for product, formulation, material/process discovery and design. * Develop advanced data-driven and physics-based models to ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ... When you ship here, you can literally watch the physics change. Under the hood, that means training ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Physics, Electrical Engineering, or related field of study * Possess solid programming skills

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Physics, Electrical Engineering, or related field of study * Possess solid programming skills

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Physics, Electrical Engineering, or related field of study * Possess solid programming skills

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Physics Informed Machine Learning information

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 Michigan?

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

What job categories do people searching Physics Informed Machine Learning jobs in Michigan look for?

The top searched job categories for Physics Informed Machine Learning jobs in Michigan are:

What cities in Michigan are hiring for Physics Informed Machine Learning jobs?

Cities in Michigan 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 Michigan as of August 2026, with employment types broken down into 6% Internship, 40% Full Time, 47% Part Time, and 7% Contract. Highlights an 100% In-person job distribution.

Materials Informatics Scientist

Freudenberg

Howell, MI • On-site

Full-time

Posted 5 days ago

Job description

Working at Freudenberg: We will wow your world!

Responsibilities:
  • Leads activities in generative AI and physics-informed machine learning for product, formulation, material/process discovery and design.
  • Develop advanced data-driven and physics-based models to guide and accelerate the development of products, materials and processes for sustainable solutions and new mobility applications.
  • Analyze and interpret materials data using advanced statistical and data mining techniques.
  • Propose, execute and defend project concepts; collaborate and plan experimental campaigns for model development, validation and deployment with Freudenberg Business Groups.
  • Identify and prioritize promising materials candidates for further investigation and development.
  • Work with a diverse range of experts, both internal and external, for developing high business impact solutions.
  • Communicate results through reports and presentations to diverse audiences (both technical and non-technical), including C level.
  • Collaborate effectively with materials scientists, engineers, and other researchers across geographic locations.
  • Collaborates with industry or academic specialists to apply the results of research and develop new techniques.
Qualifications:
  • PhD or equivalent experience in materials science, chemistry, chemical engineering, data science, computer science, physics, mechanical engineering, or a related field.
  • Minimum 3+ years of experience in computational methods for material and product design, either in industry or academia.
  • Strong knowledge of materials science fundamentals, including structure-property relationships, materials characterization, and the principles governing material properties and behavior.
  • Experience with cheminformatics, materials informatics, Generative AI, ML tools for accelerating multiscale and multiphysics simulations.
  • Proficiency in programming languages like Python, Julia, C/C++, and familiarity with SQL, MySQL, MongoDB, Flask, Azure, or other cloud technologies.
  • Ability to work independently and as part of a team.
  • Strong communication and stakeholder engagement skills.
  • International outlook and willingness to travel as a plus.
  • Excellent analytical, problem/situation analysis, and critical thinking skills
  • Ability to manage multiple projects and meet deadlines in a fast-paced, globally matrixed environment.

The Freudenberg Group is an equal opportunity employer that is committed to diversity and inclusion. Employment opportunities are available to all applicants and associates without regard to race, color, religion, creed, gender (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity or expression, national origin, ancestry, age, mental or physical disability, genetic information, marital status, familial status, sexual orientation, protected military or veteran status, or any other characteristic protected by applicable law.

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