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Physics Informed Neural Networks Jobs in Illinois

Simulation R&D Engineer

Lisle, IL · On-site

$90K - $120K/yr

Experience with advanced machine learning architectures, such as Physics-Informed Neural Networks (PINNs) etc., for physics-based modeling. * Prior exposure to AI-driven simulation frameworks such as ...

CAE Engineer

Lisle, IL · On-site

$80K - $140K/yr

Familiarity with machine learning and deep learning techniques, including physics-informed neural networks (PINNs). * Established records of publication such as patents and technical papers. This ...

R&D Engineer

Lisle, IL · On-site

$80K - $140K/yr

... physics-informed AI models and hybrid simulation workflows (e.g., reduced-order modeling, surrogate modeling, or neural operators) for real-world structural applications. Our Team At Molex, we create ...

... neural networks. * Prior experience working with AWS is a plus. * Some experience with natural ... Mathematics, Statistics, CS, Physics, MIS, Economics, Electrical Engineering, etc. * 2+ years ...

... drive data-informed decision-making across the enterprise. Oversee teams of data scientists ... methods, neural networks). * Strong proficiency in Python, SQL, and with cloud-based AI/ML ...

AI Engineer

Rosemont, IL · On-site

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

AI Engineer

Chicago, IL

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

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Physics Informed Neural Networks information

What is a physics informed neural network?

A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.

What does a physics informed neural network do?

In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.

What are the key skills and qualifications needed to thrive in physics informed neural networks?

To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.

What job categories do people searching Physics Informed Neural Networks jobs in Illinois look for?

The top searched job categories for Physics Informed Neural Networks jobs in Illinois are:

What cities in Illinois are hiring for Physics Informed Neural Networks jobs?

Cities in Illinois with the most Physics Informed Neural Networks job openings:

Infographic showing various Physics Informed Neural Networks job openings in Illinois as of August 2026, with employment types broken down into 49% Full Time, 50% Part Time, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Simulation R&D Engineer

Koch Industries

Lisle, IL • On-site

$90K - $120K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Koch Industries rating

8.0

Company rating: 8.0 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

138th of 543 rated manufacturers


Job description

Your Job
We are seeking a highly motivated engineer to develop and apply artificial intelligence and machine learning (AI/ML) techniques to accelerate structural and electrical simulations. This role bridges product development, finite element analysis (FEA), signal integrity (SI) analysis, and AI modeling, enabling faster and smarter product design.
You will work closely with domain experts in simulation and data science to explore physics-informed AI models and hybrid simulation workflows (e.g., reduced-order modeling, surrogate modeling, or neural operators) for real-world structural applications.
Our Team
At Molex, we create connections for life by enabling technologies that transform the future and improve lives. With a presence in more than 40 countries, we offer a complete range of connectivity products, services, and solutions across various industries, including data communications, medical, industrial, automotive, and consumer electronics.
Our Datacom and Specialty Solutions (DSS) team specializes in providing high speed connector solutions essential for building reliable communications equipment, catering to telecommunications, datacom, hyperscalers, cloud, data center, and storage applications. We continue to innovate to meet the demands of next-generation markets.
What You Will Do
  • Develop, implement, and validate next-generation simulation frameworks that leverage data-driven and physics-based approaches to accelerate structural and multi-physics analyses.
  • Integrate physics-informed or reduced-order models into existing FEA workflows (e.g., Abaqus, LS-DYNA, ANSYS Workbench) to enhance speed and scalability.
  • Build and calibrate surrogate models that accurately approximate high-fidelity simulations while maintaining minimal accuracy loss.
  • Automate data generation and management pipelines from FEA results to support model training, validation, and continuous improvement.
  • Analyze and balance trade-offs among model fidelity, computational efficiency, and generalization performance for different applications.
  • Evaluate and deploy emerging AI-for-simulation technologies (e.g., Altair PhysicsAI, Ansys SimAI) to accelerate structural, thermal, and electrical co-simulation and design optimization.
  • Design and enhance automated optimization workflows that couple FEA and signal integrity simulations (e.g., using ModeFrontier, ANSYS OptiSLang, or equivalent platforms).
  • Document, publish, and communicate findings to promote adoption of advanced simulation methodologies across engineering teams.

Who You Are (Basic Qualifications)
  • B.S. Degree in Mechanical Engineering, Computer Science, Data Science, or a related field.
  • Strong foundation in solid mechanics, finite element methods (FEM), and numerical modeling for structural and multi-physics applications.
  • Hands-on experience with one or more major FEA tools (e.g., Abaqus, ANSYS Workbench, LS-DYNA), including setup, analysis, and interpretation of results.
  • Proficient in Python programming, with experience in numerical and scientific computing libraries such as NumPy, SciPy, and related tools.
  • Experience with data preprocessing, model training, and validation workflows, including handling simulation datasets and building data pipelines for AI/ML applications.
  • Excellent communication skills, with the ability to convey complex technical concepts effectively to interdisciplinary teams and stakeholders.

What Will Put You Ahead
  • M.S. or Ph.D. in Mechanical Engineering, Computer Science, Data Science, or a related field, with a strong focus on computational modeling or AI applications.
  • Experience with advanced machine learning architectures, such as Physics-Informed Neural Networks (PINNs) etc., for physics-based modeling.
  • Prior exposure to AI-driven simulation frameworks such as PhysicsAI, SimAI, or equivalent platforms.
  • Background in reduced-order modeling (ROM), surrogate modeling, or Bayesian calibration, with experience in integrating these approaches into simulation workflows.
  • Familiarity with CAD/CAE automation and data pipelines for simulation-driven design and optimization.
  • Proven ability to translate research concepts into practical, deployable solutions in engineering or simulation contexts.
  • Strong record of technical contributions, such as peer-reviewed publications, patents, or conference presentations.

For this role, we anticipate paying $90,000 - $120,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.
Hiring Philosophy
All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here .
Who We Are
As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before.
At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.
Our Benefits
Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter.
Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.
Equal Opportunities
Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here , aquí , or tu ).
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