Process Modeling

2 weeks ago

Lahore, Punjab, Pakistan Enginerify Full time 1,200,000 - 3,600,000 per year

About the Role

We are looking for a Machine Learning & CFD Engineer to join our team for practical, industry-driven projects combining Computational Fluid Dynamics (CFD) and Machine Learning (ML). The engineer will work on building Digital Twin models, reduced-order modeling (ROM), and predictive ML models for chemical engineering and industrial processes.

This role involves not just model development but collaboration with industry clients on real-world challenges, such as temperature field prediction, combustion analysis, and process optimization.

Key Responsibilities

  • Preprocess and analyze CFD simulation data for ML workflows.
  • Implement PCA, Autoencoders (AE), POD-ROM, and AT-ROM techniques for dimensionality reduction and surrogate modeling.
  • Train ML models (MLP, LSTM, regression methods) for prediction of unseen cases.
  • Integrate ML models into Digital Twin frameworks for industrial processes.
  • Collaborate with clients on data validation, model deployment, and visualization.

Qualifications

  • Bachelor's/Master's in Chemical Engineering, Mechanical Engineering, or related field.
  • Experience with CFD tools (ANSYS Fluent, and Python ML libraries (Scikit-learn, TensorFlow, PyTorch).
  • Strong foundation in numerical modeling, fluid dynamics, and data analysis.
  • Hands-on experience with ROM methods (POD, AE) and predictive modeling preferred.
  • Ability to work with cross-functional teams and deliver project milestones.

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