PhD Position in Numerical Multiscale Mechanics and Deep Material Networks, University of Duisburg-Essen, Germany

Summary

The University of Duisburg‑Essen invites applications for a PhD position in numerical multiscale mechanics and deep material networks within the DFG‑funded project on creep behavior of inorganic sand cores. The role involves developing voxel‑based microstructure models, performing FFT‑based simulations, quantifying uncertainties, and advancing deep material networks. Candidates will work at the Institute for Engineering Mathematics, collaborate with the University of Augsburg, and publish their results. The position is salaried under TV‑L EG 13 (gross €59,324‑€84,319), lasts three years, and offers full‑time or part‑time options. Required qualifications include a university degree of at least eight semesters, strong background in computational mechanics, programming skills in Python and C/C++, and very good English. The university provides extensive research infrastructure, flexible working conditions, and a supportive, family‑friendly environment.

Key Facts

About the Project

The DFG‑funded project aims to model the creep behavior of inorganic sand cores using microstructure‑driven approaches. In collaboration with the University of Augsburg, the team will develop voxel‑based microstructure models for porous sand‑binder systems, simulate viscoelastic, creep, damage and strength phenomena at the micro‑scale, and validate results against experimental data. Advanced FFT‑based simulations, uncertainty quantification, and deep material networks will be employed to create predictive tools for component simulations, culminating in a doctoral thesis and scientific publications.

Key Responsibilities

• Develop voxel‑based microstructure models for porous sand‑binder systems
• Model viscoelasticity, creep, damage and strength at the microstructural scale
• Perform FFT‑based microstructure simulations and compare results with experimental data
• Develop efficient methods for quantifying microstructure‑induced uncertainties
• Advance Deep Material Networks for porous, time‑dependent and damaging materials
• Implement, document and publish the developed methods and software
• Present results at scientific conferences and publish in peer‑reviewed journals

Required Skills

• Strong knowledge of continuum mechanics, numerical mechanics or scientific computing
• Programming experience, preferably Python and C or C++
• Very good written and spoken English
• Ability to work independently, structured and careful
• (Desirable) Experience in numerical homogenization, FFT methods, time‑dependent material models, damage mechanics, model order reduction or machine learning

Who Should Apply

Applicants with a university degree (minimum eight semesters) in computational mechanics, mechanical engineering, civil engineering, materials science, applied mathematics or a related field, who possess solid knowledge of continuum and numerical mechanics, programming experience in Python and C/C++, and very good English skills (German is a plus) are encouraged to apply. Candidates should be self‑motivated, structured, and interested in interdisciplinary research on microstructure‑based material modeling.

Benefits

• Clearly defined DFG‑funded PhD project with methodological and industrial relevance
• Access to high‑performance computing infrastructure and established software for microstructure modelling, FFT simulations and Deep Material Networks
• Secure public‑service employment with reliable conditions
• Respectful and appreciative work environment
• Opportunity to obtain a PhD with extensive support offerings
• Diverse training and continuing‑education programmes
• Campus cafeteria and Mensa services
• Attractive corporate‑benefits discounts
• Family‑friendly university culture (childcare, care advice)
• Excellent public‑transport connections and free parking
• Flexible / sliding working hours and possibility of home office
• 30 days vacation plus additional days on Christmas Eve and New Year’s Eve
• Fair remuneration according to TV‑L tariff, including annual special payment and company pension
• Extensive sports and health offers

About the Employer

The University of Duisburg‑Essen describes itself as a young, innovative university in the Ruhr metropolitan area, distinguished in research and teaching, committed to diversity, and fostering a respectful, appreciative community.