PhD - A Generator of Optimized Winding Schemes in Electrical Machines

In this role you will develop advanced mathematical methods to model pin winding systems for innovative electric machine designs. You will formulate robust representations of complex boundary conditions and manufacturing constraints, and assess the efficiency of discrete optimization algorithms. You will integrate models into simulation tools to evaluate winding schemes against key performance indicators. This position offers a chance to impact next-generation electric machines within a collaborative Bosch environment.

• Develop a novel mathematical approach to model hairpin winding systems for electric machines
• formulate robust representations of boundary conditions, symmetry, operating conditions, and manufacturing constraints
• analyze the computational complexity, feasibility, and runtime of discrete optimization algorithms
• integrate mathematical models into existing simulation tools to evaluate and optimize winding schemes using defined KPIs

• Master in Applied Mathematics (or equivalent) or related fields
• experience in optimization, especially discrete optimization
• experience with electromagnetic field simulation and applying math to real-world problems, ideally with electric machines
• hands-on knowledge of object-oriented programming
• proficient in MATLAB and Python
• experience with version control (Git) and Visual Studio
• fluent in English; German or willingness to learn

• analytical problem solving
• open-minded and forward-thinking
• clear communication
• discrete optimization
• electromagnetic field simulation
• mathematical modeling