Salary: 62.000 - 67.000 € per year Requirements: masters degree in mechanical engineering, materials science, computational engineering, computer science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural networks using common Python-ML libraries such as PyTorch background knowledge in computational mechanics and materials science highly proficient in spoken and written English Responsibilities: development of novel machine models based on supervised, unsupervised and reinforcement learning that can be combined with, enhance or replace methods from computational engineering and computer simulation data modeling and assimilation towards experimental measurements under consideration of uncertainties utilization of Explainable AI techniques to enable novel scientific discoveries explore and evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results in international scientific journals and at international conferences and workshops Technologies: AI Machine Learning PyTorch Python Mobile More: We are the Helmholtz-Zentrum Hereon, conducting cutting-edge international research for a changing world. With around 1,000 employees from more than 60 nations, we tackle challenges like climate change and the sustainable use of coastal systems. Our Institute of Material and Process Design focuses on the sustainable development of innovative materials and manufacturing processes, particularly for sectors like transportation and medical technology. We offer an exciting and varied job, a well-connected research campus, opportunities for further training, social benefits, and excellent compatibility of private and professional life, making us a family-friendly workplace. last updated 16 week of 2026