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Computational Modeling Simulation Multiphysics Jobs in New York

Aaru

Simulation Engineer

New York, NY · On-site

$250K - $800K/yr

  • Medical

  • Dental

  • Vision

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 ...

SteelStone

Aerodynamic Simulation Engineer

Brooklyn, NY · On-site

$110K - $140K/yr

The engineer will create models to inform the design of products sold in mass retail channels. Job ... Use computational fluid dynamics (CFD) tools to predict airflow patterns and thermal effects.

SteelStone

Aerodynamic Simulation Engineer

Brooklyn, NY · On-site

$110K - $140K/yr

The engineer will create models to inform the design of products sold in mass retail channels. Job ... computational fluid dynamics (CFD) tools to predict airflow patterns and thermal effects. • ...

Aaru

Population Simulation Researcher

New York, NY · On-site

$250K - $800K/yr

  • Medical

  • Dental

  • Vision

You have deep experience with synthetic data generation, agent-based modeling, computational social ... You are interested in using LLMs as a simulation substrate - not just for text generation, but for ...

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All JobsComputational Modeling Simulation Multiphysics JobsComputational Modeling Simulation Multiphysics Jobs in New York

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
Infographic showing various Computational Modeling Simulation Multiphysics job openings in New York as of August 2026, with employment types broken down into 100% Full Time. Highlights an 49% In-person, and 51% Remote job distribution.

Simulation Engineer

Aaru

New York, NY • On-site

$250K - $800K/yr

Full-time

Medical, Dental, Vision

Re-posted 16 hours ago

Job description

ABOUT AARU
Aaru operates at the frontier of predictive intelligence, using AI to simulate and predict human behavior at scale. By generating and deploying instances of artificial intelligence that mirror humans, called agents, Aaru simulates entire populations with unprecedented accuracy. Our partners use Aaru to refine strategic positioning, identify and understand high-value audiences, validate concepts and messaging before launch, optimize pricing decisions, and build a continuously richer understanding of their customers through simulation. We provide organizations with invaluable foresight, empowering them to anticipate outcomes and proactively make the right decisions at the right time, every time.
We're a small, dedicated, mission-driven team and we intend to stay that way. We believe the best work happens when exceptionally talented people are given ownership, trust and the space to operate without bureaucratic friction. We work with urgency and intellectual honesty and expect new team members to match our velocity. We seek individuals who thrive at the frontier, who push beyond conventional limits, who bring curiosity and conviction in equal measure, and who want their work to have demonstrable impact in the world. If you're energized by the idea of a small team doing things that feel impossible, let's build together.
ABOUT THE ROLE
Simulation Engineering owns the path from research idea to production system. Researchers prove out how to synthesize an audience, model a world, predict responses, score accuracy, or ship a result; you turn those ideas into robust, reusable, fast code - the objects, contracts, evaluations, and workflows that produce the product.
RESPONSIBILITIES
  • Productionize the core simulation loop - audience generation, world modeling, response prediction.
  • Design the reusable abstractions that the product is made of: agent and population objects, simulation contracts and interfaces, evaluation harnesses, etc.
  • Build and own evaluation and accuracy infrastructure.
  • Make simulations fast and cheap enough to run at scale.
  • Partner closely with Simulation Research to harden hybrid LLM + classical architectures.
  • Build the workflows and tooling that let deployment and forward-deployed teams stand up new client simulations.
  • Create the calculation, analysis, and publication layers that turn raw agent output into the decision-ready artifacts customers see.
  • Hold the line on engineering quality across a fast-moving codebase.

YOU MAY BE A FIT IF
  • You have deep expertise in ML and AI, with meaningful prior work using Large Language Models in production systems
  • You've designed and run rigorous ML experiments, moving from hypothesis to evaluation to deployment
  • You have 3+ years of hands-on experience building ML/AI systems (research or applied)
  • You're comfortable working across the full model lifecycle: data collection, training, evaluation, and production integration
  • You have experience working cross-functionally with engineering and product teams to ship ML-powered features
  • You're deeply curious and motivated to push the boundaries of what simulation technology can do
STRONG CANDIDATES MAY ALSO
  • Have publications at top ML venues (NeurIPS, ICML, ICLR, ACL)
  • Have experience building or fine-tuning multi-agent systems
  • Have worked on probabilistic modeling, Bayesian inference, or causal reasoning
  • Have familiarity with our stack or demonstrate the ability to learn unfamiliar technologies quickly
  • Have direct experience with simulation, agent-based modeling, Monte Carlo methods, or other modeling-and-prediction systems.
  • Have experience with hybrid architectures that combine LLMs with classical statistical or ML methods.
  • Have background in a quantitative or data-heavy domains - quant finance, computational social science, ad measurement, forecasting, statistics, or psychometrics.
  • A research sensibility: comfort reading papers, prototyping alongside researchers, and contributing to or co-authoring published work.
LOCATION
This role is based in New York City. Aaru is an in-person company, working 5 days a week in office. Candidates are expected to be located within the New York City metropolitan area or open to relocation.
BENEFITS
At Aaru, we take care of our people. In addition to a competitive base salary and equity participation, we offer comprehensive medical, vision, and dental coverage, visa sponsorship and relocation support, and various other benefits and perks.

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