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Computational Modeling Simulation Multiphysics Jobs in Boston, MA

1910

Computational Theoretical Chemist I

Boston, MA

... molecular dynamics simulations are changing the way we develop new drugs. At 1910 , we put ... Validate a cellular hit in a clinically relevant animal model of disease * Update provisional ...

SES

Computational Materials Scientist

Woburn, MA · On-site +1

As a Computational Materials Scientist, you will be a core data-driven modeler responsible for ... Atomistic Modeling & Simulation * Conduct and oversee DFT (Density Functional Theory), MD ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

... molecular dynamics simulation are changing the way we develop new drugs. At 1910 , we put ... Validate a cellular hit in a clinically relevant animal model of disease * Update provisional ...

1910

Computational Theoretical Chemist I

Boston, MA

... molecular dynamics simulations are changing the way we develop new drugs. At 1910 , we put ... Validate a cellular hit in a clinically relevant animal model of disease * Update provisional ...

1910

Computational Theoretical Chemist I

Boston, MA · On-site

... molecular dynamics simulations are changing the way we develop new drugs. At 1910 , we put ... Validate a cellular hit in a clinically relevant animal model of disease * Update provisional ...

1910

Computational Theoretical Chemist III

Boston, MA · On-site

... molecular dynamics simulation are changing the way we develop new drugs. At 1910 , we put ... Validate a cellular hit in a clinically relevant animal model of disease * Update provisional ...

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Computational Modeling Simulation Multiphysics information

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$42.4K

$110K

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

As of May 29, 2026, the average yearly pay for computational modeling simulation multiphysics in Boston, MA is $110,004.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $140,700.00 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 are popular job titles related to Computational Modeling Simulation Multiphysics jobs in Boston, MA? For Computational Modeling Simulation Multiphysics jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Boston, MA look for? The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Boston, MA are:
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Computational Modeling Simulation Multiphysics jobs near you

Research Scientist I/II, Multiscale & Multiphysics Simulations

Lila Sciences

Cambridge, MA • On-site

Other

Posted 14 days ago

Job description

Your Impact at LILA

Your role will focus on building next-generation in silico multiphysics and multiscale simulation capabilities that power AI-driven scientific discovery. You will develop high-fidelity digital representations of complex physical systems spanning chemical and mechanical processes, transport phenomena, and electromagnetic behavior and integrate them into autonomous discovery and experimental pipelines.

You will work on integrating simulation methods-such as finite element modeling, computational fluid dynamics, phase-field methods, and TCAD-style transport/process modeling-into scalable, programmatic, and agent-driven systems that enable real-time digital twins, simulation-informed decision-making, and autonomous closed-loop workflows

What You'll Be Building

  • Develop and deploy robust multiphysics models across coupled domains (e.g., thermal, fluid, structural, electromagnetic, chemical), using methods such as coarse-grained, mesoscale, FEM, and CFD techniques.
  • Build integrated multiscale frameworks that connect atomistic, mesoscale, and continuum representations to model materials and devices.
  • Design and implement programmatic, agent-driven simulation workflows that can autonomously configure, execute, and refine simulations within closed-loop discovery workflows.
  • Create scalable, GPU-accelerated simulation pipelines, data infrastructure, and interoperable APIs that connect commercial tools (e.g., COMSOL, ANSYS) and custom solvers deploying on cloud-based, high-throughput computing environments
  • Collaborate with AI, software, and automation teams to orchestrate and deploy closed-loop discovery workflows, integrating computational predictions with robotic and cloud-based laboratory platforms to enable automated experiment-simulation feedback cycles and accelerated R&D.

What You'll Need to Succeed

  • PhD in Mechanical Engineering, Chemical Engineering, Aerospace Engineering, Materials Science, or a related field.
  • Extensive experience with multiphysics simulation methods and numerical algorithms, including FEM, CFD, TCAD/process simulation, mesoscale modelling, or related techniques.
  • Strong foundation in coupled physical phenomena, including heat transfer, fluid dynamics, structural mechanics, mass transport, diffusion, electromagnetism, and reaction kinetics.
  • Experience applying simulation to real-world systems in industrial settings such as semiconductors, chemical processing, aerospace, or materials manufacturing.
  • Solid programming skills in Python and building simulation workflows, automation pipelines, or custom numerical models.

Bonus Points For

  • Experience bridging atomistic simulations with one or more additional simulation domains including coarse-grained, finite-element and continuum models.
  • Familiarity with machine learning approaches applied to physical simulations (e.g., surrogate models, neural operators, physics-informed neural networks), along with experience leveraging GPU acceleration and programmatic optimization for scalable simulations
  • Experience integrating simulation frameworks into digital twin systems, real-time decision environments, or closed-loop control workflows.
  • Background applying simulation to complex materials and process domains such as thin-film deposition, micro/nano-fabrication, or reactive transport, with an understanding of processing-structure-property relationships.

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