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Computational Modeling Simulation Multiphysics Jobs in Chicago, IL

Leverage Computational Fluid Dynamics (CFD) to analyze and improve flow behavior in valves and ... Experience with CFD tools and simulation methods * Proficiency in CAD software (SolidWorks ...

Leverage Computational Fluid Dynamics (CFD) to analyze and improve flow behavior in valves and ... Experience with CFD tools and simulation methods * Proficiency in CAD software (SolidWorks ...

Leverage Computational Fluid Dynamics (CFD) to analyze and improve flow behavior in valves and ... Experience with CFD tools and simulation methods * Proficiency in CAD software (SolidWorks ...

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Computational Modeling Simulation Multiphysics information

See Chicago, IL salary details

$40.2K

$104.3K

$148.3K

How much do computational modeling simulation multiphysics jobs pay per year?

As of May 30, 2026, the average yearly pay for computational modeling simulation multiphysics in Chicago, IL is $104,308.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,900.00 and $133,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Modeling Simulation Multiphysics Engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What are some common challenges faced by professionals in Computational Modeling Simulation Multiphysics roles, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Chicago, IL look for? The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Chicago, IL are:
Postdoctoral Appointee - Data Infrastructure and Software for AI

Postdoctoral Appointee - Data Infrastructure and Software for AI

Argonne National Laboratory

Lemont, IL • On-site

$70.76K - $117.93K/yr

Full-time

Posted 25 days ago


Job description

The Argonne Leadership Computing Facility's (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community. We help researchers solve some of the world's largest and most complex problems with our unique combination of supercomputing resources and computational science expertise.
The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference, the ALCF is studying the application of these techniques to a variety of our science applications, including but not limited to: Computational Chemistry, Plasma Physics, High Energy Physics, analysis of Light Source data such as that from the Advanced Photon Source, Biology, Astronomy, and other science disciplines.
The chosen applicant will have a rare chance to work on exascale supercomputing systems and novel AI hardware to help solve significant real-world problems using machine learning and deep learning. ALCF researchers work in a highly collaborative environment involving science application teams, academia and industry, as well as other national labs and agencies, to solve some of the world's largest and most complex problems in science and engineering.
Objective:
  • The goal for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems.
  • The postdoc will work on multimodal data management for science applications, focusing on integrating, organizing, and analyzing diverse data types to accelerate scientific discovery and innovation.
  • Another goal is to develop and evaluate vector databases and retrieval-augmented generation (RAG) and integrate agentic AI systems to meet the demands of large-scale fine-tuning and inference.
  • The postdoc will also work on design and implement agentic-AI workflows using the Model Context Protocol (MCP) to orchestrate data ingest and data movement across heterogeneous storage systems, including object stores.
  • The postdoc will also engage with science application teams and contribute to broader initiatives, including the American Science Cloud (AmSC) AI Services efforts, and to help us with design of future systems and data-management solutions to meet needs of our applications.

Benefit to ALCF:
This postdoc position will help ALCF evaluate and integrate data infrastructure needed to better facilitate AI models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help prototype, benchmark, and evaluate strategies to better support these workloads for Aurora.
Position Requirements
Required skills and qualifications:
  • A recent PhD (completed within the last 0-5 years) in computer science, computational science, a physical science, engineering, or related field
  • Comprehensive experience programming in one or more programming languages such as Python, C/C++
  • Experience with at least of one of the AI frameworks is required, such as PyTorch, TensorFlow
  • Ability to create, maintain, and support high-quality software is essential
  • Work with and contribute to domain-specific software and models
  • Experience with version control software such as git is essential
  • Effective written and oral communications skills
  • Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork

Preferred skills and qualifications:
  • Experience with running simulations or AI workflows on supercomputers
  • Experience with training or applying large language models for research
  • Experience with MPI and Input/Output (I/O), and data management
  • Experience in writing technical papers and presentations

Job Family
Postdoctoral
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
The expected hiring range for this position is $70,758.00-$117,925.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.