Simulation Automation & Python Development for Process simulations in Welding and Additive Manufacturing

We are a cross-disciplinary research group focusing on the intersection of theoretical
physics, finite element analysis (FEA), and Scientific Machine Learning (SciML). We are currently
upgrading our core simulation infrastructure for welding and manufacturing processes.
To support our downstream algorithms (including microstructure prediction, super-resolution neural
networks, and reinforcement learning), we are migrating away from legacy black-box software to a modern,
fully automated workflow using Ansys and the PyAnsys ecosystem. We are looking for a highly
motivated engineering undergraduate to help us build this automated Python interface.
This is a strictly theoretical and computational role—no physical lab work is
required. You will be responsible for building the “data engine” that feeds our advanced predictive models.
Your core tasks will include:
• Workflow Automation: Develop Python scripts using ansys-mapdl-core (PyMAPDL) to fully
automate the Ansys meshing process and moving heat source definitions without relying on the GUI.
• Data Pipeline Development: Utilize the Ansys Data Processing Framework (PyDPF) to efficiently
extract raw thermal and mechanical field data (temperature, stress, strain) from binary .rst
files.
• API Integration: Build clean, modular Python wrappers to format the extracted finite element
data into NumPy arrays/HDF5, enabling weak-coupling with our proprietary microstructure and
hardness prediction algorithms.
• Documentation & Visualization: Generate automated3D visualizations (using PyVista) and
document the code to ensure smooth team collaboration.