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Computational Modeling Simulation Multiphysics Jobs in Pennsylvania

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... computing, modeling, simulation, systems, or data analysis approaches applied to biological or ... Computational and Data Sciences (including advanced computing infrastructure), the Materials ...

Cornelis Networks

Mechanical Engineer

Wayne, PA · On-site

The ability to effectively focus a significant amount of computational power on solving critical problems through the use of artificial intelligence, data analytics, and modeling/simulation ...

Cornelis Networks, Inc.

Mechanical Engineer

Wayne, PA · On-site

The ability to effectively focus a significant amount of computational power on solving critical problems through the use of artificial intelligence, data analytics, and modeling/simulation ...

Cornelis Networks

Mechanical Engineer

Wayne, PA · Hybrid

The ability to effectively focus a significant amount of computational power on solving critical problems through the use of artificial intelligence, data analytics, and modeling/simulation ...

Cornelis Networks

Mechanical Engineer

Wayne, PA · On-site

The ability to effectively focus a significant amount of computational power on solving critical problems through the use of artificial intelligence, data analytics, and modeling/simulation ...

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Computational Modeling Simulation Multiphysics information

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 are common challenges faced by professionals in computational modeling simulation multiphysics, 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 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 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.

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Computational Modeling Simulation Multiphysics jobs near you

Staff Engineer - AI/ML & Digital Twin

Synopsys Inc

Canonsburg, PA • On-site

Full-time

Re-posted 18 days ago

Job description

Job Summary:
Synopsys Inc, part of Ansys, is a global leader in engineering simulation software. They are seeking a Staff Engineer with expertise in AI/ML and digital twin technologies to lead technical engagements and develop innovative solutions that enhance engineering workflows and democratize simulation technology.
Responsibilities:
• Lead and execute technical engagements across the customer lifecycle, including discovery, solution development, demonstrations, evaluations, and deployment.
• Engage directly with customers to understand engineering workflows, data availability, and decision-making processes, translating them into AI-enabled simulation and digital engineering solutions.
• Develop and implement differentiated solutions using technologies such as automation, reduced order modeling, optimization, simulation democratization, system-level modeling, and digital twins.
• Integrate machine learning models within simulation and digital twin pipelines to improve prediction accuracy, reduce computational cost, and enable near real-time insights.
• Define and deliver automated and scalable workflows that reduce reliance on expert-driven simulation and enable broader adoption across engineering teams.
• Lead or contribute to first-of-a-kind or ambiguous use cases, including AI-assisted design exploration, surrogate modeling, and digital twin deployment.
• Collaborate closely with product development teams to influence roadmap, validate new capabilities, and improve usability of AI-enabled features.
• Deliver professional services, training, and technical guidance to ensure successful adoption of advanced workflows.
• Support pre-sales and technical marketing activities through demonstrations, evaluations, and industry engagement.
• Mentor team members and contribute to the best internal practices around AI, automation, and simulation integration.
Qualifications:
Required:
• MS (or PhD) in Engineering, Computer Science, Applied Mathematics, or related field.
• 5+ years of experience in engineering systems, simulation, or data-driven modeling.
• Strong programming skills (Python preferred).
• Experience working with modeling, simulation, optimization, or data-driven engineering workflows.
• Strong analytical, problem-solving, and communication skills.
• Ability to operate effectively in a customer-facing, consultative engineering role.
• Proven experience in automation of engineering workflows or pipelines using tools such as optiSLang, modeFrontier, HEEDS or equivalent.
• Demonstrated expertise applying machine learning techniques in engineering contexts, including surrogate modeling, regression methods, or neural networks (CNNs, RNNs, autoencoders).
• Understanding of projection-based ROMs, dimensionality reduction, and feature engineering.
• Knowledge of multi-fidelity system modeling using Twin Builder, Simulink, AMESim or equivalent.
• Familiarity with deployment and operationalization of AI models, including integration into engineering workflows and use of frameworks such as PyTorch, TensorFlow, scikit-learn, Kubernetes, AWS/Azure equivalent.
• Exposure to cloud or HPC-based environments for large-scale simulation or data processing.
Company:
Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. Founded in 1986, the company is headquartered in Mountain View, USA, with a team of 10001+ employees. The company is currently Late Stage.
Synopsys logo

About Synopsys

Sourced by ZipRecruiter

Synopsys, Inc. (Nasdaq:SNPS) is the Silicon to Software partner for creative companies developing the electronic products and software applications we rely on every single day. As the world's 15th largest software company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and is also growing its leadership in software quality and security solutions. Whether you're a system-on-chip (SoC) designer building advanced semiconductors, or a software developer writing applications that require the highest quality and security, Synopsys has the solutions needed to deliver exceptional, secure products for the era of connected everything. The company is headquartered in Mountain View, California, and has approximately 113 offices located throughout North America, South America, Europe, Japan, Asia and India. Since 1986, Synopsys has been at the heart of accelerating electronics innovation with engineers around the world having used Synopsys technology to successfully design and create billions of chips and systems that are found in the electronics that people rely on every single day.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Mountain View, CA, US

Year founded

1986

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