PhD Student – Multi-Objective Optimization, Additive Manufacturing

Stellenbeschreibung:

Research and develop novel multi-objective optimization methods for additive manufacturing
Analyze the potential and limitations of existing optimization tools and methods, including GI-MDTO, COMSOL Multiphysics, and Synera
Develop new design methodology approaches for interdisciplinary functional integration
Advance simulation-based methods for multi-objective optimization
Integrate optimization, simulation, and manufacturing requirements into a holistic methodology
Validate developed approaches through practical applications using LEOPARD and selected additive manufacturing processes
Create multidisciplinary, functionally integrated components while considering technical and manufacturing constraints
Contribute to reducing development and cycle times and increasing production-equipment efficiency

Requirements

Good to very good university degree qualifying for doctoral studies in mechanical engineering, automotive engineering, production engineering, computational engineering, mechatronics, or a comparable field
Knowledge of design, simulation, optimization, or additive manufacturing
Interest in scientific research and complex technical challenges
Excellent analytical skills
Independent, structured approach to work
German or English language level B1
Confirmation of supervision by a professor
Confirmed delimitation of topics by a professor of a university or research institution entitled to confer a doctorate
Experience with CAE methods, numerical simulation, or optimization software is stated as ideal, not required

Core Competencies

Demonstrates expertise in multi-objective optimization methods for additive manufacturing, integrating simulation and manufacturing requirements while validating approaches through practical applications. Proficient in design, simulation, and optimization with a strong analytical mindset and structured work approach.