Computational Physics Engineer

2 Months ago • All levels • Physics Engine

Job Summary

Job Description

Develop physics models for HVAC systems, occupant behavior, and comfort simulation using Computational Fluid Dynamics. Create numerical models and software development using Swift. Use knowledge of thermodynamics, heat transfer, and fluid dynamics. Validate the Building Simulator against EnergyPlus and real-world sensor data. Automate testing using Python or Swift. Utilize optimization algorithms for tasks like state estimation. Collaborate with the AI Control team for integration. Debug geometry model import tools such as EPJSONConverter.
Must have:
  • Master’s degree in Mechanical Engineering
  • Experience in Building Energy Engineering
  • Proficiency in Heat Transfer, Fluid Dynamics, and Thermodynamics
  • Experience with Numerical Modeling & Optimization
  • Experience with Computational Fluid Dynamics
  • Experience with EnergyPlus
  • Proficiency in Swift or Python

Job Details

Description:

Capture high fidelity physics of HVAC systems, occupants and comfort simulation, ground simulation, air mixing (using Computational Fluid Dynamics), advanced glazing etc. in a building thermal zone to expand the capabilities of our Building Simulator product. Create both mathematical or numerical models and software development in programming language like Swift. Develop models using understanding of thermodynamics, heat transfer, and fluid dynamics. Validate the Building Simulator against EnergyPlus and real-world sensor data. Automate the testing and validation process using suitable programming language such as Python, Swift, etc. Use Optimization algorithms coupled with Differentiable Programming for tasks like State Estimation, Model Tuning, etc. Collaborate with AI Control team for seamless integration of various simulators (Building Simulator, Equipment Simulator, Comfort Simulator) with our controller. Debug tools used for building geometry model imports like EPJSONConverter.

Requires: 

Master’s Degree in Mechanical Engineering, plus at least 6 months experience in Building Energy Engineering, and proficiency with Heat Transfer, Fluid Dynamics, Thermodynamics, Numerical Modeling & Optimization, Computational Fluid Dynamics, EnergyPlus, and Swift or Python.

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PassiveLogic enables autonomy for controlled systems and unlocks collaboration between teams to manage those systems. PassiveLogic has reimagined how we design, build, operate, maintain, and manage infrastructural robots, whose current technology has remained unchanged for decades. By using revolutionary physics-based Quantum digital twins and leveraging the world’s fastest AI compiler to simulate future-forward controls, PassiveLogic empowers users to easily create their own generative digital twins in minutes to launch autonomous control.

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