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Computational Modeling Simulation Multiphysics Jobs in Kearny, NJ

Computational Plasma Physicist

Kearny, NJ · On-site

$120K - $140K/yr

Conduct simulations and analysis of fusion plasma behavior in stellarators, using advanced computational models. * Collaborate with cross-disciplinary teams to refine designs and improve the ...

Computational Plasma Physicist

Kearny, NJ · On-site

$120K - $140K/yr

Conduct simulations and analysis of fusion plasma behavior in stellarators, using advanced computational models. * Collaborate with cross-disciplinary teams to refine designs and improve the ...

Job Responsibilities: * Assist in developing and implementing risk and credibility assessment frameworks for NAMs, including computational models, mechanistic experiments/simulations, organoid models ...

Computational Designer

New York, NY · On-site

$115K - $143K/yr

EDEN is a digital design environment for the engineering and design of ecosystems , modeling the ... EDEN enables designers to plan intentionally for these outcomes through analysis, simulation, and ...

... simulation, and data analysis and interpretation. The trainee will build skills in scientific ... The project integrates experimental biomechanics and computational modeling to develop a platform ...

Simulation Engineer

New York, NY · On-site

$200K - $540K/yr

Researchers prove out how to synthesize an audience, model a world, predict responses, score ... Have background in a quantitative or data-heavy domains - quant finance, computational social ...

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Computational Modeling Simulation Multiphysics information

See Kearny, NJ salary details

$40.8K

$105.9K

$150.6K

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

As of Jul 10, 2026, the average yearly pay for computational modeling simulation multiphysics in Kearny, NJ is $105,870.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,100.00 and $135,400.00 per year, depending on experience, location, and employer.

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 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 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 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.
Infographic showing various Computational Modeling Simulation Multiphysics job openings in Kearny, NJ as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $105,870 per year, or $50.9 per hour.
Research Scientist - Quantum & AI Photonic Chip Simulation

Research Scientist - Quantum & AI Photonic Chip Simulation

QCi

Hoboken, NJ • On-site

Full-time

Re-posted 18 days ago


Job description

Location: Hoboken, NJ
Department: Tomorrow
Reports to: Ting Bu
Position Overview
The Research Scientist will work on the modeling, simulation, and architectural development of
quantum and artificial intelligence (AI) computational structures intended for chip-scale
implementation. This role focuses on translating advanced quantum and AI concepts into
physically realistic, simulation-validated device and system designs suitable for fabrication. It
concentrates on high-fidelity simulation, feasibility analysis, and performance optimization under
practical fabrication constraints. The role serves as a technical bridge between the research
team developing novel quantum/AI architectures and the chip fabrication team responsible for
implementation, ensuring that proposed designs are physically realizable, scalable, and
performance-optimized prior to tape-out.
Duties and Responsibilities
• Develop and simulate quantum and AI-based photonic architectures for on-chip
implementation.
• Translate high-level computational concepts into device-level and system-level
simulation models.
• Perform rigorous electromagnetic and multiphysics simulations to evaluate optical,
nonlinear, and quantum effects.
• Model and simulate quantum photonic circuits and quantum gates under realistic device
conditions.
• Analyze fabrication tolerances and material constraints to assess design robustness.
Optimize photonic device structures for performance, scalability, and manufacturability.
• Collaborate closely with fabrication and packaging teams to ensure simulation models
align with process capabilities.
• Support post-fabrication validation by correlating experimental results with simulation
predictions.
• Document modeling methodologies, simulation results, and architectural trade-offs for
internal and external reporting.
Required Qualifications
Education
• Ph.D. in Physics, Applied Physics, Electrical Engineering, or a closely related discipline.
Technical Background
• Strong foundation in Photonics, Quantum optics, Nonlinear optics
• Demonstrated experience in simulation of photonic integrated circuits.
• Experience modeling and simulating quantum gates or quantum optical systems.
• Understanding of semiconductor/TFLN and photonic chip fabrication processes sufficient
to incorporate realistic constraints into simulations.
• Familiarity with chip testing and packaging considerations from a modeling perspective.
Software Proficiency
• Lumerical (FDTD, MODE, INTERCONNECT)
• Tidy3D
• COMSOL Multiphysics
• Python
• MATLAB