Master’s thesis in the field Automated Design Optimization in the Digital Modeling Department “Gradient-based Optimization of Parameterized CAD Geometries with PDE Constraints”, 6-7 months

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Master’s thesis in the field Automated Design Optimization in the Digital Modeling Department “Gradient-based Optimization of Parameterized CAD Geometries with PDE Constraints”, 6-7 months

• Introductory training in adjoint formulations and domain decompositions in the context of PDE constrained optimization
• Introductory training in the open source finite element software Netgen/NGSolve
• Software development of an adjoint-based algorithm for parameterized design optimization in Netgen/NGSolve (Python)
• Application of the algorithm to Freudenberg specific use cases (e.g., sealing parts with nonlinear material behavior)
• Documentation and interpretation of optimization results

• You are studying mathematics, computational engineering or mechanical engineering
• Solid knowledge in nonlinear optimization and the finite element method
• Knowledge in optimization with partial differential equations desirable
• Python programming experience preferable
• Previous experience with Netgen/NGSolve is a plus
• Excellent analytical skills
• Interest in optimization theory and practice
• Affinity for programming and engineering applications
• Very good German and/or English language skills (oral and in writing)

Cafeteria/ Canteen

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Public Transportation Allowance

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Sustainability & Social Commitment

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Employee discounts

Opportunities for deals on products and services.