Ph.D. Position in Safe Reinforcement Learning for Autonomous Spacecraft Systems (m/f/d)

Ph.D. Position in Safe Reinforcement Learning for Autonomous Spacecraft Systems (m/f/d)

, Academic staff

Applications are invited for a fully funded PhD position exploring the intersection of reinforcement learning, space‑craft dynamics, and formal verification within the newly established Professorship of Spacecraft Control (Prof. Dr. Niklas Kochdumper), affiliated with the Department of Aerospace and Geodesy.

Motivation

Future space missions increasingly rely on autonomous decision‑making due to communication delays, uncertain environments, and mission complexity. Applications such as planetary landing, autonomous docking, formation flying, and on‑orbit servicing demand control policies that are adaptive, data‑efficient, and robust to uncertainties. Reinforcement learning has shown significant promise in these domains by enabling agents to learn complex control strategies directly from interaction with the environment. However, standard reinforcement learning methods lack formal safety guarantees, making them unsuitable for safety‑critical space applications where constraint violations can lead to catastrophic mission failure. To bridge this gap, safe reinforcement learning methods have emerged, combining learning‑based control with explicit safety mechanisms. Among these, shielding approaches, which enforce safety constraints by filtering or correcting control actions, offer a promising path toward safe‑by‑construction autonomy.

This PhD project aims to develop theoretically grounded and practically viable reinforcement learning frameworks for spacecraft systems, where safety is guaranteed at all times through shielding, while still allowing learning‑based performance optimization.

Your Tasks

• Develop reinforcement learning solutions for spacecraft control tasks, such as autonomous docking, planetary landing, and active debris removal (requires experience with reinforcement learning).
• Implement high‑fidelity simulation environments that can be used to train the reinforcement learning agents (requires solid knowledge about the underlying spacecraft dynamics).
• Integrate shielding methods into the training and application process to provide formal safety guarantees, even in the presence of uncertainties (requires strong mathematical background).
• Contribute to the design and development of spacecraft test facilities for the experimental validation of reinforcement learning approaches (requires basic knowledge about hardware, sensors, actuators, etc.).
• Design and execute experimental campaigns in a laboratory environment to evaluate the performance of the reinforcement learning agents.

Your Responsibilities

• Publish research findings in high‑impact international journals, present at leading conferences, and support in the preparation of research proposals.
• Mentor undergraduate and master students.
• Develop expertise and stay up‑to‑date with the latest advancements in this research area.
• Support in establishing a new professorship.
• Contribute to teaching and examinations for TUM students at the Professorship of Spacecraft Control.
• Participate in administrative tasks at the Professorship of Spacecraft Control.

Your Profile

• Above‑average master’s degree in Aerospace Engineering, Mechanical Engineering, Robotics, Physics, Mathematics, or a closely related field.
• Strong foundations in spacecraft dynamics and control theory as well as experience with reinforcement learning.
• Good programming skills in Python and/or MATLAB (C++ is a plus).
• Strong interest in independently investigating scientific research questions.
• Excellent teamwork capability.
• Fluency in spoken and written English.

The successful candidate must fulfill the requirements for admission to a Ph.D. program at TUM. More information on a doctorate at TUM can be found on the websites of the TUM Graduate School and of the Graduate Center of Engineering and Design.

What we offer

• Full‑time position (100% / 40h, pay grade E13, TV‑L) with an initial 2‑year contract (renewable up to 6 years), and the goal to obtain a Ph.D.
• You work at one of the most prestigious universities in Europe in an excellent, internationally connected environment and actively help shape innovative scientific developments.
• Close supervision and support for developing an independent research profile.
• Opportunities to publish in leading journals and present at international conferences.

The position is based at the TUM Ottobrunn Campus in the vicinity of Munich, Bavaria, Germany.

Application

Send all required documents in an email with subject "PHD‑SCC‑1‑(your name)" to until 1st of May 2026.

• Letter of motivation (1 page maximum)
• Curriculum Vitae including publication list if applicable
• Academic transcripts and degree certificates (BSc and MSc)
• Master's thesis or exemplary research report (if you have not yet graduated, you can upload an exemplary research report or publication)

The position is suitable for people with severe disabilities. Severely disabled applicants will be given preference if they are otherwise essentially equally qualified, capable, and professionally competent. TUM is an equal opportunity employer and aims to increase the proportion of women in the workforce.

Data Protection Information

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Contact

Technical University of Munich
School of Engineering and Design
Professorship of Spacecraft Control
Prof. Dr. Niklas Kochdumper
Caroline‑Herschel‑Str. 100, 85521 Ottobrunn