Internship/Master thesis Quantum Machine Learning for Crashworthiness Optimization

What to expect In crashworthiness optimization, we aim to design vehicles that are robust, safe, and lightweight. Evaluating these designs is computationally expensive, so we use surrogate models to approximate costly simulations. However, mathematical bottlenecks within the surrogate modeling process can limit efficiency and accuracy. In this Master’s thesis, you will explore how quantum algorithms can accelerate and enhance surrogate modeling, gaining hands-on experience with quantum machine …

Currently enrolled in a Master’s program in Computer Science, Physics, Mathematics, Engineering, or a related field.

Strong background in machine learning and optimization.

Knowledge of quantum computing and quantum algorithms is highly desirable.