PhD Position on Physics-Guided Digital Twin Development for Magnesium Alloys

The Institute of Material and Process Design at Helmholtz-Zentrum Hereon invites applications for a 4-year doctoral position focusing on computational materials engineering. The project aims to create a physics-guided digital twin framework for magnesium alloys by bridging mechanistic simulations with data-driven machine learning approaches. The successful candidate will work in an interdisciplinary team to model composition-process-structure-property relationships across various manufacturing conditions. Responsibilities include building simulation workflows, validating predictions against experimental data, and contributing to next-generation Integrated Computational Materials Engineering methodologies. Applicants are expected to hold a master's degree in a relevant discipline and demonstrate strong programming and analytical skills.

• Develop physics-guided machine-learning models to predict composition-process-structure-property relationships in magnesium alloys
• Integrate crystal plasticity, phase-field, precipitation, and machine-learning techniques into a unified digital twin framework
• Implement simulation and machine-learning workflows using Python libraries such as PyTorch and Scikit-Learn
• Incorporate experimental microstructure and texture characterization data obtained from optical microscopy, SEM, EBSD, XRD, and mechanical testing
• Investigate uncertainty quantification and explainable artificial intelligence methods for advanced materials modeling
• Validate computational predictions in close collaboration with experimental and modeling researchers
• Publish and present scientific results in leading international journals, conferences, and workshops