Master Thesis (f/m/x) - Development of ML-Algorithms for Guidance and Control

The Institute of Space Systems in Bremen is dedicated to designing and analyzing future spacecraft and space missions, including launchers, orbital and exploration systems, and satellites. Our evaluations focus on the technical feasibility, performance and costs of these systems, utilizing a range of cutting-edge, multi-disciplinary engineering methods.

What To Expect

Machine Learning (ML) is becoming increasingly important for enhancing the autonomy and performance of spacecraft and launch vehicles. In Guidance and Control (G&C), ML-based methods such as Deep Reinforcement Learning offer promising capabilities but often lack interpretability and provable stability — key requirements for safety-critical aerospace applications. To address these limitations, the project investigates how explainability, interpretability, and stability guarantees can be embedded directly into ML-based control design. Genetic Programming (GP) is one potential approach, as it can produce human-readable models and incorporate stability considerations during optimization. Your work will explore and extend such methods to develop ML algorithms capable of generating interpretable and stable control laws. The results aim to enable reliable ML-supported G&C systems for future space missions.

Your tasks

• study the theoretical foundations of GP, model interpretability/ explainability, and stability analysis
• develop a GP-based algorithm capable of generating stable and interpretable control laws
• validate the algorithm on a simple benchmark problem (e.g., inverted pendulum on a cart)
• apply the method to a selected aerospace guidance or control scenario

Your profile

• Bachelor’s degree in Aerospace Engineering, Mechanical Engineering, or Computer Science
• good knowledge of the Python programming language
• basic understanding of control theory
• interest in machine learning methods for dynamical systems
• ability to work independently and analytically

We look forward to getting to know you! If you have any questions about this position (Vacancy-ID 3717) please contact:

Dr. Francesco Marchetti
Tel.: