PhD position on Physics-Guided Digital Twin Development for Composition-Process-Structure-Property M

Cutting-edge Research Um sich zu bewerben, lesen Sie sich einfach die folgende Stellenbeschreibung durch und fügen Sie die relevanten Dokumente bei. PhD position on Physics-Guided Digital Twin Development for Composition-Process-Structure-Property Modeling of Magnesium Alloys The Institute of Material and Process Design at the Helmholtz-Zentrum Hereon is offering a 4-year PhD position in the field of computational materials engineering, machine learning, and digital twins for advanced lightweight materials. The focus of the PhD project will be the development of a physics-guided digital twin framework for magnesium alloys by integrating experimental characterization, crystal plasticity, phase-field modeling, precipitation modeling, and machine learning approaches to establish quantitative composition-process-structure-property relationships. Building upon recently developed machine-learning approaches for structure-property prediction in extruded magnesium alloys, the project aims to advance toward a next-generation Integrated Computational Materials Engineering (ICME) framework capable of predicting microstructure evolution and resulting mechanical properties across previously unseen processing conditions and material states. The objective of the project is to bridge the gap between purely data-driven materials modeling and mechanistic microstructure simulations by combining crystal plasticity, dynamic recrystallization, precipitation kinetics, and machine learning into a unified digital-twin framework. The resulting methodologies shall enable accelerated alloy and process design by leveraging experimentally validated physics-guided surrogate models with improved extrapolation capabilities beyond the limits of conventional machine-learning approaches. We would therefore strongly encourage qualified women to apply for the position. development of physics-guided machine-learning models for composition-process-structure-property relationships in magnesium alloys implementation of simulation and machine-learning workflows in Python (e.g. PyTorch, Scikit-Learn, etc.) incorporation of experimental microstructure and texture characterization data obtained from optical microscopy, SEM, EBSD, XRD, and mechanical testing publication and presentation of scientific results in leading international journals, conferences, and workshops master's degree in mechanical engineering, materials science, computational engineering, physics, applied mathematics, data science, or a related discipline good programming skills in Python experience with machine-learning methods and common scientific Python libraries is desirable experience in analysis of experimental materials-science data is beneficial highly proficient in spoken and written English an International Welcome Office with guest accommodation ~social benefits under the collective agreement for the German public sector and remuneration up to pay grade 13 (EntgO Bund) ~ very good work-life balance; a well-connected research campus, good networking opportunities, a subsidized Deutschlandticket (job ticket) subject to certain conditions, and charging facilities for electric vehicles ~ PhD Buddy Program ~ a family-friendly working environment with childcare options, e.g. a daycare center close to the workplace ~ workplace health promotion programmes, e.g. an Employee Assistance Program (EAP) ~ corporate benefits ~ The Helmholtz-Zentrum Hereon conducts cutting-edge international research for a changing world: The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative materials and manufacturing processes, especially for the transportation sector and medical technology. Then we are looking forward to receiving your comprehensive application documents (cover letter, CV, transcripts, certificates, etc.)