PhD Researcher in Physics-Based Machine Learning for Materials and Process Design | PhD position on physics-based machine learning modeling for materials and process design

Job Summary

This 4-year PhD position at the Helmholtz-Zentrum Hereon focuses on bridging the gap between classical computational engineering and modern artificial intelligence. As a doctoral researcher, you will develop advanced machine learning models—including supervised, unsupervised, and reinforcement learning—to enhance or replace traditional finite element methods and constitutive material models. Your day-to-day work involves implementing ML pipelines in Python, utilizing Explainable AI (XAI) to uncover scientific insights, and exploring system architectures like Retrieval-Augmented Generation (RAG) for data retrieval. You will work across the composition-process-structure-property-performance chain to enable stable manufacturing of lightweight structures. This role is highly attractive for researchers seeking a cross-disciplinary environment, offering a public service contract (TV-L E13), a dedicated PhD Buddy Program, and the opportunity to publish in international journals while benefiting from a family-friendly research campus with flexible working conditions.