Work environment

Our casting development team at the Kassel site, together with the Large Casting Competence Center, plays a leading role within the group in shaping the casting products and processes of the future. A key focus is the optimization of gating systems to further improve the quality, efficiency, and reproducibility of casting processes. Together with you, we aim to develop a methodology that enables systematic evaluation and optimization of gating systems for large cast parts. Become part of our team – we’re excited to meet you!

Possible tasks within this role

• Develop and validate a methodology for optimizing gating systems for large cast components
• Investigate and apply topological and parametric optimization methods to design efficient gating geometries
• Evaluate developed concepts in terms of castability, thermal stress, and susceptibility to defects
• Consider real-world defect patterns in the optimization results
• Integrate the developed methodology into existing development processes and tools

Qualification requirements

• Master’s degree students in Mechanical Engineering, Materials Science, Computer Science, Mathematics, or a related field
• Good to very good academic performance
• Basic knowledge of casting technology and/or flow simulation, as well as programming skills (preferably in Python), is desirable
• Experience with optimization methods (e.g., topology optimization, parametric optimization) and simulation software (e.g., Flow3D, MAGMASOFT, OpenFOAM) is a plus
• Ability to work independently and solve problems experimentally
• German language skills at B2 level, English at B1 level

The following documents muust be submitted with your application

• Curriculum Vitae
• Current certificate of enrollment
• Current academic transcript
• Work permit for non-EU citizens
• In case of a compulsory internship, a certificate from the university

Keywords

Production Informatics, Computational Engineering, CAE (Computer-Aided Engineering), Design Automation, Thermomechanical Analysis, Machine Learning in Engineering, Digital Twin, Additive Manufacturing, Finite Element Analysis (FEA), Sustainable Manufacturing