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Physics Based Machine Learning Jobs in Utah (NOW HIRING)

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

Machine Learning Tutor

Logan, UT · Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

Machine Learning Tutor

Provo, UT · Remote

$18 - $40/hr

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... For US based candidates, the base pay ranges for a successful candidate are listed below.

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... For US based candidates, the base pay ranges for a successful candidate are listed below.

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... For US based candidates, the base pay ranges for a successful candidate are listed below.

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... For US based candidates, the base pay ranges for a successful candidate are listed below.

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... For US based candidates, the base pay ranges for a successful candidate are listed below.

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Physics Based Machine Learning information

What types of projects or problems does a Physics Based Machine Learning professional typically work on?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.

What is a Physics Based Machine Learning job?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

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

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What cities in Utah are hiring for Physics Based Machine Learning jobs? Cities in Utah with the most Physics Based Machine Learning job openings:
Infographic showing various Physics Based Machine Learning job openings in Utah as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, and 6% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.
R&D Data Scientist

R&D Data Scientist

Hexcel Corporation

Salt Lake City, UT • On-site, Remote

Full-time

Posted 22 days ago


Hexcel rating

7.5

Company rating: 7.5 out of 10

Based on 19 frontline employees who took The Breakroom Quiz


Job description

With our strong investment in research and development and our culture of continuous improvement, Hexcel is the industry leader in the manufacturing of advance composite materials, including carbon fiber, woven reinforcements, resins, prepregs, honeycombs and engineered core and composite structures. We invite you to join the Hexcel team at various manufacturing sites, sales offices and R&D centers around the globe. Become a part of the "strength within."

Hexcel is currently seeking aResearch and Development Data Scientistfor ourSalt Lake City, UT, USA. This person will lead the development and deployment of digital twin technologies that accelerate material, process, and product innovation.This role will focus on building virtual representations of manufacturing processes, materials, and products using advanced analytics, machine learning, physics-based modeling, and AI. The successful candidate will bridge physical experimentation and digital simulation to improve process performance, reduce development cycles, and support next-generation composite material technologies.

The selected individual will be responsible for but not limited to the following obligations:

  • Lead the design, development, validation, and deployment of digital twins for manufacturing processes, material systems, and product development programs.
  • Develop hybrid modeling approaches that combine physics-based models, first-principles engineering, machine learning, and statistical methodologies.
  • Integrate sensor, process, quality, and operational data into digital twin frameworks to improve predictive capabilities and decision-making.
  • Design and implement advanced AI, machine learning, and analytics solutions that enhance model accuracy, process control, and product performance.
  • Collaborate with scientists, engineers, technicians, and manufacturing teams to translate physical system behavior into scalable digital twin architectures.
  • Support experimentation strategies, including Design of Experiments (DOE), active learning, and closed-loop optimization to continuously improve digital twin performance.
  • Develop simulation environments for evaluating process changes, material innovations, and manufacturing outcomes before physical implementation.
  • Establish model governance practices including validation, uncertainty quantification, monitoring, and lifecycle management of digital twin applications.
  • Communicate digital twin insights and recommendations to technical and business stakeholders to drive data-driven innovation and operational excellence.

Required Qualifications

  • Master's degree in data science, Materials Science, Chemical Engineering, Mechanical Engineering, Applied Mathematics, Physics, or a related technical discipline.
  • Minimum 2+ years of experience developing predictive models, digital twins, simulation tools, or advanced analytics solutions in an industrial environment.
  • Demonstrated experience creating and validating digital twin or virtual process models using machine learning, statistical modeling, physics-based modeling, or hybrid approaches.
  • Experience modeling complex physical, chemical, or manufacturing systems.
  • Strong analytical and problem-solving skills with the ability to connect physical processes to data-driven modeling techniques.
  • Proficiency in Python, R, or similar programming languages and associated machine learning ecosystems.
  • Experience with cloud-based data and AI platforms, preferably Microsoft Azure.
  • Strong communication skills with the ability to explain complex modeling concepts to multidisciplinary teams.
  • Eligible candidates must be a U.S. citizen.

Preferred Qualifications

  • Experience with Digital Twin platforms, Industrial IoT architectures, or digital thread initiatives.
  • Experience with Azure Digital Twins, Azure Machine Learning, Azure IoT, Microsoft Fabric, Synapse, or related Microsoft technologies.
  • Experience working with manufacturing data, process optimization, materials development, or composite materials.
  • Familiarity with ML Ops, model deployment, model governance, and continuous monitoring frameworks.
  • Experience utilizing large language models (LLMs), generative AI, or AI agents to support engineering and scientific workflows.
  • Experience applying AI and optimization techniques to material formulation or chemical composition development

Eligible candidates must be a: U.S. citizen, U.S. national, person lawfully admitted for permanent residence, temporary resident under sections 210(a) or 245(A) of the Immigration and Nationality Act, person admitted in refugee status, or person granted asylum. Hexcel (NYSE: HXL) is a global leader in advanced composites technology, a leading producer of carbon fiber, and the world leader in honeycomb manufacturing for the commercial aerospace industry.

Hexcel is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, physical or mental disability, status as a protected veteran, or any other protected class.


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