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Computational Modeling Simulation Multiphysics Jobs in Massachusetts

Develop and execute test methods and simulation models to mitigate design risks and ensure product ... Exposure to computational modeling, fluid dynamics, and hemocompatibility testing. * Experience ...

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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.

What are popular job titles related to Computational Modeling Simulation Multiphysics jobs in Massachusetts?

For Computational Modeling Simulation Multiphysics jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Massachusetts look for?

The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Massachusetts are:

What cities in Massachusetts are hiring for Computational Modeling Simulation Multiphysics jobs?

Cities in Massachusetts with the most Computational Modeling Simulation Multiphysics job openings:

Infographic showing various Computational Modeling Simulation Multiphysics job openings in Massachusetts as of August 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 87% In-person, 4% Hybrid, and 9% Remote job distribution.

Data Scientist - Simulation (Senior - Principal)

Symbotic

Wilmington, MA • On-site

$149 - $204.60/hr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 29 days ago


Symbotic rating

7.2

Company rating: 7.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

184th of 244 rated software companies


Job description

USA Wilmington, MA - HQ

Data Scientist – Simulation (Senior - Principal) What we need

We are seeking an experienced Senior or Principal Data Scientist to lead the development of advanced simulation models that power next‑generation robotic warehouse systems. In this role, you will build high‑fidelity simulations of large‑scale robotic fleets, optimize system performance, and inform strategic product and operational decisions.

This is a highly cross‑functional position spanning data science, robotics, operations research, and distributed systems, where your work will directly impact efficiency, throughput, and scalability of real‑world automation systems.

What we do

We design, test, and deploy advanced robotic systems that improve warehouse throughput, efficiency, and reliability at scale. By reducing reliance on physical testing, we accelerate innovation cycles and drive significant operational savings and productivity gains across real‑world production environments. Our team tackles complex automation and optimization challenges alongside world‑class engineers and scientists, with the opportunity to directly influence cutting‑edge systems deployed in the field.

Your responsibilities
  • Design and develop simulation frameworks for robotic warehouse systems, including robot fleets, inventory flows, task allocation, and human‑robot interaction.
  • Build discrete‑event and agent‑based simulations to model complex, stochastic environments at scale.
  • Develop predictive and prescriptive models to optimize throughput, latency, and resource utilization.
  • Partner with robotics, software, and operations teams to evaluate new algorithms (routing, task assignment, scheduling), test system changes before production deployment, identify bottlenecks and failure modes.
  • Create digital twins of warehouse environments to enable scenario testing and capacity planning.
  • Apply machine learning and statistical techniques to improve simulation realism and calibration.
  • Deliver clear insights and recommendations to technical and executive stakeholders.
  • Establish best practices for model validation, experimentation, and reproducibility.
Required Qualifications
  • MS or PhD in Computer Science, Data Science, Operations Research, Applied Mathematics, Physics, or related field.
  • Minimum of 5 years (Senior) or 8 years (Principal) in simulation, modeling, or systems optimization.
  • Experience with complex, distributed systems.
  • Strong experience with Discrete‑event simulation (DES) or agent‑based modeling.
  • Python (NumPy, Pandas, SciPy) and/or simulation frameworks (SimPy, AnyLogic, Arena, or custom tools).
  • Solid understanding of probability, stochastic processes, and statistics.
  • Optimization techniques (LP, MIP, heuristics, metaheuristics).
  • Experience working with large datasets and building data pipelines.
  • Ability to translate real‑world system behavior into computational models.
Preferred Qualifications
  • Robotics, warehouse automation, logistics, or supply chain systems.
  • Fleet optimization or multi‑agent systems.
  • Reinforcement learning for decision‑making.
  • Path planning, task allocation, and scheduling algorithms.
  • Digital twin architecture.
  • Experience with C++ or high‑performance systems for large‑scale simulation.
  • Knowledge of cloud platforms (AWS, Azure, GCP) and distributed computing.
  • Background in experimentation platforms or A/B testing in operational systems.
Principal‑Level Expectations
  • Define and drive the long‑term simulation and modeling strategy.
  • Architect scalable simulation platforms used across the organization.
  • Influence product and operational strategy through data‑driven insights.
  • Mentor and grow a team of data scientists and engineers.
  • Serve as a subject matter expert in simulation, optimization, and system modeling.
Tech Stack
  • Python (NumPy, Pandas, SciPy, SimPy).
  • Data platforms (Snowflake, Databricks).
  • Visualization (Grafana, Tableau).
  • Cloud infrastructure (GCP).
  • Optional: Python, C#, and C++.
Our environment
  • Up to 10% travel may be required. Employees must have a valid driver’s license and the ability to drive and/or fly to client and other customer locations.
  • The employee is responsible for owning a credit card and managing expenses personally to be reimbursed on a bi‑weekly basis.
Compensation and Benefits

The base range for this position in the posted location is $149,000.00 - $204,600.00; however, base pay offered may vary depending on job‑related knowledge, skills, and experience. The compensation package includes medical, dental, vision, disability, 401K, PTO and/or other benefits.

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