Are you passionate about using simulations to solve complex problems, test theories, and optimize performance? Do you enjoy creating virtual environments that mimic real-world conditions for industries ranging from robotics and automotive to aerospace and manufacturing? If you're ready to design realistic simulations that provide actionable insights, our client has the perfect role for you. We're looking for a Simulation Engineer (aka The Virtual Problem Solver) to build, validate, and optimize simulation models that enhance product development and decision-making.
As a Simulation Engineer at our client, you'll collaborate with engineers, designers, and analysts to create virtual prototypes, simulate environments, and test scenarios in controlled settings. Your expertise in physics, modeling, and computational analysis will be essential in developing simulations that are accurate, reliable, and informative.
Key Responsibilities: Design and Develop Simulation Models: Create and implement simulation models that replicate real-world systems, processes, or physical behaviors. You'll work with tools like MATLAB, Simulink, or Ansys to develop simulations that align with project goals and industry standards. Conduct System and Process Simulations: Run simulations to test designs, predict system behavior, and optimize performance. You'll analyze results to inform design decisions and identify areas for improvement or further testing. Collaborate on Virtual Prototyping and Testing: Work closely with design and engineering teams to create virtual prototypes, enabling cost-effective testing and analysis. You'll help validate design concepts before physical testing, reducing development time and costs. Optimize Models for Accuracy and Performance: Calibrate simulation models to improve accuracy, reliability, and computational efficiency. You'll refine parameters and settings to ensure realistic outcomes that meet project requirements. Validate Simulation Data with Real-World Testing: Compare simulation results with physical tests to validate model accuracy and consistency. You'll use feedback from field testing to fine-tune models and increase predictive reliability. Document Simulation Processes and Findings: Maintain detailed documentation of simulation models, methodologies, and results. You'll ensure that findings are accessible for future reference, analysis, and potential replication. Stay Updated on Simulation Tools and Techniques: Continuously research advancements in simulation technology, tools, and methodologies. You'll incorporate new techniques and tools to improve model quality and efficiency.Required Skills: Proficiency in Simulation and Modeling Tools: Strong experience with simulation software such as MATLAB, Simulink, Ansys, or COMSOL Multiphysics. Knowledge of Physics and Engineering Principles: Deep understanding of mechanics, thermodynamics, fluid dynamics, or electrical principles as they apply to simulation and modeling. Programming Skills in Python, C++, or MATLAB: Proficiency in scripting languages for developing simulation scripts, automating processes, and optimizing model performance. Analytical and Problem-Solving Skills: Ability to interpret simulation data, troubleshoot model issues, and refine simulations for improved accuracy and relevance. Attention to Detail and Documentation: Strong organizational skills for documenting simulation setups, findings, and parameters for reliable, reproducible results. Educational Requirements: Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, Physics, Computer Science, or a related field. Equivalent experience in simulation engineering may be considered. Certifications or coursework in simulation software, computational modeling, or virtual prototyping are advantageous. Experience Requirements: 3+ years of experience in simulation engineering or computational modeling, with a portfolio of simulations that demonstrate high-quality, accurate results. Familiarity with real-world testing and validation, including comparison of simulation results with physical data. Experience in industries such as automotive, aerospace, robotics, or manufacturing is a plus.
#J-18808-Ljbffr