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Physics Simulation Python Jobs in Florida (NOW HIRING)

Proficiency in Python; comfortable writing simulation tooling, test harnesses, and automation scripts. * Experience with at least one physics engine: PhysX, MuJoCo, Bullet, or Drake. * Solid ...

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Physics Simulation Python information

What is the difference between Physics Simulation Python vs Mechanical Engineer?

AspectPhysics Simulation PythonMechanical Engineer
Required CredentialsProgramming skills, knowledge of physics, often a degree in physics or computer scienceMechanical engineering degree, professional licensure in some regions
Work EnvironmentSoftware development, research labs, simulation environmentsDesign offices, manufacturing plants, R&D departments
Industry UsageSimulation software development, research, academiaProduct design, manufacturing, systems optimization

Physics Simulation Python focuses on developing and implementing physics-based simulations using Python programming, often in research or software development contexts. Mechanical Engineers apply engineering principles to design, analyze, and manufacture mechanical systems. While both roles require a strong understanding of physics, Physics Simulation Python emphasizes coding and simulation, whereas Mechanical Engineering involves practical design and application in physical systems.

Does NASA hire physicists?

Yes, NASA hires physicists for roles involving research, space science, and engineering projects. These positions often require advanced degrees in physics or related fields and familiarity with scientific tools and data analysis methods. Physicists at NASA contribute to mission development, data interpretation, and technological innovation.

What are the key skills and qualifications needed to thrive as a Physics Simulation Python Developer, and why are they important?

To excel as a Physics Simulation Python Developer, you need a strong background in physics, mathematics, and proficiency in Python programming, often supported by a degree in physics, engineering, or computer science. Familiarity with simulation libraries (such as NumPy, SciPy, PyBullet, or SimPy), version control systems like Git, and experience with visualization tools are commonly required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills in this role. These skills enable the development of accurate, efficient simulations and foster productive teamwork in research or engineering projects.

What are some common challenges faced by professionals working in Physics Simulation with Python, and how can they be addressed?

Professionals in Physics Simulation with Python often encounter challenges such as optimizing simulation performance, ensuring numerical accuracy, and integrating complex libraries (e.g., NumPy, SciPy, PyBullet) into larger workflows. Addressing these issues typically involves using efficient coding practices, leveraging vectorized operations, and validating results with analytical solutions or experimental data. Collaboration with domain experts and regular code reviews can also help maintain code reliability and project scalability. Staying updated with the latest simulation frameworks and actively participating in open-source communities are excellent ways to overcome technical hurdles.

Is Python still in demand in 2026?

Python remains highly in demand for physics simulation roles in 2026 due to its versatility, extensive libraries like NumPy and SciPy, and strong community support. Professionals skilled in Python, along with knowledge of scientific computing and simulation frameworks, are sought after in research, engineering, and development environments.

Who hires computational physicists?

Computational physicists are hired by research institutions, government laboratories, universities, and private industry companies involved in scientific research, technology development, and simulation modeling. They often work in fields such as aerospace, defense, energy, and software development, utilizing programming skills and scientific expertise to solve complex physical problems.

What is a Physics Simulation Python developer?

A Physics Simulation Python developer is a professional who uses the Python programming language to design, implement, and analyze simulations that model physical systems and phenomena. These simulations can range from simple particle motion to complex fluid dynamics or electromagnetic fields, and are widely used in research, engineering, gaming, and education. The developer typically utilizes scientific libraries such as NumPy, SciPy, and PyBullet, and may also work with visualization tools to present simulation results. Their work helps in understanding real-world physics problems, testing hypotheses, or creating realistic interactive environments.

Is Python good for physics simulation?

Physics simulation Python roles often require knowledge of Python libraries such as NumPy, SciPy, and PyBullet, which are well-suited for modeling physical systems. Python's ease of use, extensive scientific computing ecosystem, and ability to integrate with other tools make it a popular choice for developing and running physics simulations in research and industry. Proficiency in numerical methods and understanding of physics principles are also important for these positions.
What cities in Florida are hiring for Physics Simulation Python jobs? Cities in Florida with the most Physics Simulation Python job openings:

Robotics Simulation Engineer

Persona AI

Pensacola, FL • On-site

Full-time

Re-posted 3 days ago


Job description

We're looking for a Simulation Engineer to own and expand our NVIDIA Isaac Sim and Omniverse simulation infrastructure. You'll build the digital twin environments, sim assets, and CI/CD pipelines that our autonomy team relies on daily. You will help achieve the vision in which every robot behavior we develop is prototyped, tested, and validated in simulation before it runs on hardware.
As a simulation engineer at Persona, you will have an incredible opportunity to shape the simulation infrastructure that underpins our entire autonomy stack. You will report to the Behavior Coordination Lead and work closely with machine learning, locomotion, manipulation, perception, and devops teams.
Your Role:
  • Build, maintain, and extend simulation environments in NVIDIA Isaac Sim and Omniverse for humanoid robot development.
  • Develop and manage OpenUSD sim assets: robot models, tools, workpieces, customer facility environments (shipyards, steel fabrication plants, industrial sites).
  • Create and maintain physics-accurate digital twins of customer facilities (shipyards and industrial manufacturing) for behavior validation and deployment planning.
  • Integrate all autonomy subsystems (locomotion, manipulation, perception, hands, navigation, welding) to run against Isaac Sim.
  • Design and implement behavior-level CI/CD pipelines that automatically validate robot behaviors in simulation.
  • Prototype and mock-test robot behaviors (welding, navigation, manipulation) in simulation before hardware integration.
  • Develop synthetic data generation pipelines for training perception, manipulation, and navigation models.

We're Looking For:
  • BS, MS, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
  • 3+ years of professional experience in robotics simulation, digital twin development, or physics-based simulation environments.
  • Strong hands-on experience with NVIDIA Isaac Sim and/or NVIDIA Omniverse.
  • Working knowledge of OpenUSD (Universal Scene Description): authoring, composition, referencing, flattening, and debugging USD stage hierarchies.
  • Proficiency in Python; comfortable writing simulation tooling, test harnesses, and automation scripts.
  • Experience with at least one physics engine: PhysX, MuJoCo, Bullet, or Drake.
  • Solid understanding of robot kinematics, dynamics, and articulated body simulation.
  • Experience developing or maintaining CI/CD pipelines for simulation or robotics software.
  • Familiarity with containerization (Docker) and DevOps practices for simulation infrastructure.
  • Ability to create and manage 3D simulation assets (meshes, materials, collision geometry, articulation definitions).

Preferred or Bonus Qualifications:
  • Experience with NVIDIA Isaac Lab for reinforcement learning environment setup and training.
  • Familiarity with NVIDIA Cosmos for synthetic data generation and scene variability.
  • Experience with ROS/ROS 2 and Gazebo simulation.
  • Experience with Unreal Engine or other real-time rendering engines for robotics visualization.
  • Background in manipulation simulation: contact modeling, grasp planning, dexterous multi-fingered hand interaction, and force/torque estimation.
  • Experience with motion capture data pipelines and motion retargeting to robot models.
  • Exposure to behavior trees, task planning, or autonomy stack architecture.
  • Knowledge of Omniverse extensions development and Kit SDK.