PhD position: ML based implementation of constitutive behavior of stainless steel
Job Summary
Metal forming is a widely used method to form steel products efficiently in mass manufacturing. As steel is highly recyclable, its usage helps in creating a more sustainable world. For simulations of industrial processes concerning such complex materials, one must rely on continuum models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel possesses complex microstructures across various length scales and different phases, leading to nonlinear time and history-dependent material behavior. Additionally, innovative changes in steel production, especially toward green steel, require precise prediction of properties for industrial applications.
This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behavior of materials. The goal is to create material models based on advanced ML methods and integrate them into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, enhancing time and cost efficiency in production pipelines.
Responsibilities
- Develop hybrid machine learning material models.
- Integrate these models into Finite Element Modelling (FEM).
- Capture complex, nonlinear, path- and history-dependent material behavior.
Qualifications and Requirements
- A master’s degree in mechanical engineering, materials science, computer science, applied mathematics, or a related field.
- A strong background in machine learning, material modeling, and metals processing, modeling, and simulation.
- Experience with programming languages (e.g., Python, MATLAB) and simulation software.
- Excellent academic record.
- A dynamic, creative, and pioneering professional attitude with a willingness to work in a strongly interdisciplinary team and learn cross-disciplinary foundations.
- Strong communication skills (fluent in English, both oral and written), with specific English proficiency requirements such as IELTS overall score of 6.5 or higher, TOEFL computer-based score of at least 237, or internet-based score of at least 92.
What the Employer Offers
- A full-time position (1.0 FTE) of four years, starting with a temporary contract of one year, renewable for another three years based on progress.
- A salary ranging from €2,901 gross per month in the first year to a maximum of €3,707 gross per month in the fourth year.
- A holiday allowance of 8% gross annual income and an 8.3% year-end bonus.
- Enrollment in the Graduate School of Science and Engineering for PhD training.
- The preferred starting date is 1 January 2026.
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