PhD Position: Advanced Onboard Control Systems for Spacecraft with AI (m/f/d)

PhD Position: Advanced Onboard Control Systems for Spacecraft with AI (m/f/d)

26.06.2024, Wissenschaftliches Personal

Join our research team to focus on advancing spacecraft control systems through AI-driven AOCS. This PhD position involves developing innovative control strategies using machine learning and other AI techniques to enhance spacecraft autonomy and responsiveness in dynamic environments.

About us and the position

Spacecraft Advanced Onboard Control Systems (AOCS) play a critical role in ensuring the stability, manoeuvrability, and functionality of spacecraft during their missions. Traditionally, AOCS rely on pre-programmed algorithms and human intervention to navigate, orient, and control spacecraft systems. Artificial Intelligence (AI) technologies have emerged as a promising approach to enhance the capabilities of spacecraft AOCS. The integration of AI technologies into spacecraft AOCS opens new possibilities for enhancing mission autonomy, adaptability, and efficiency. By leveraging machine learning, neural networks, and other AI techniques, spacecraft can overcome the challenges of operating in complex and unpredictable space environments, paving the way for future breakthroughs in space exploration, science, and technology.

Join our research team to focus on advancing spacecraft control systems through AI-driven AOCS. This PhD position involves developing innovative control strategies using machine learning and other AI techniques to enhance spacecraft autonomy and responsiveness in dynamic environments. The PhD is conducted in collaboration with Klepsydra (https://klepsydra.com/). Klepsydra Technologies is a leading provider of AI on the edge software solutions that empower organisations to harness the full potential of artificial intelligence. With a commitment to innovation and excellence, Klepsydra team of experts develops cutting-edge AI software for various industries, including space exploration, robotics, automotive, and more.

Required Skills & Experience

• Master’s degree in Aerospace Engineering, Electrical Engineering, Computer Science, or a related field.

• Strong background in control systems, robotics, machine learning, or AI.

• Proficiency in programming languages such as Python, MATLAB, or C/C++.

• Excellent analytical and problem-solving skills.

• Ability to work both independently and collaboratively in a team environment.

• Prior research experience and publications in relevant areas will be advantageous.

• Excellent communication skills, both written and spoken in English

Responsibilities

Your main responsibilities will be the following

• Research and identify existing AI algorithms applicable to spacecraft AOCS, including but not limited to machine learning, deep learning, reinforcement learning, and evolutionary algorithms.

• Develop a comprehensive understanding of spacecraft dynamics, control systems, and mission requirements to inform the selection and adaptation of AI algorithms for AOCS applications.

• Design and implement AI-based control algorithms for spacecraft AOCS, considering factors such as robustness, adaptability, real-time performance, and compatibility with onboard hardware.

• Conduct simulation-based studies to evaluate the performance of AI-driven AOCS algorithms across a range of use-cases, including orbital manoeuvring, attitude control, rendezvous and docking, and autonomous navigation.

• Validate the effectiveness and scalability of developed algorithms through hardware-in-the-loop (HIL) testing and/or integration with actual spacecraft platforms or testbeds.

• Investigate and address challenges related to the integration of AI algorithms into spacecraft AOCS, such as computational constraints, sensor noise, environmental uncertainties, and safety considerations.

• Compare and benchmark the performance of AI-based AOCS algorithms against traditional control methods and state-of-the-art approaches, highlighting their advantages and limitations in different mission scenarios.

• Publish research findings in peer-reviewed journals and present results at relevant conferences and workshops to contribute to the advancement of knowledge in the field of spacecraft AOCS and AI.

• Document and disseminate research outcomes, methodologies, and best practices through technical reports, white papers, and open-access repositories to benefit the broader scientific community and facilitate future research endeavors in the field.

What we offer

Full position (100% / 40h / E13) with a 3 year contract

30 days of paid holidays

An amazing team and the possibility of getting involved in something big

A large network of people in the space business

We value diversity, equity, and inclusion and encourage candidates from underrepresented groups to apply. We are dedicated to offering an inclusive research environment and encourage applicants of all backgrounds to apply, including individuals with disabilities. The position is suitable for disabled persons.

Application

Interested candidates should send their application (incl. CV, motivation letter (max. 1 page), current and past transcript of records, as well as any supporting documents) via E-Mail at: rfa-jobs.rfa@ed.tum.de (preferably in a single PDF). We look forward to your application.

The vacancy will be open until filled

The position shall start in September 2024

Data Protection Information:

As part of your application, you provide personal data to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm to have read and understood the data protection information provided by TUM.

Technische Universität München

TUM School of Engineering and Design

Chair of Space Mobility and Propulsion

Prof. Dr.-Ing. Chiara Manfletti

Lise-Meitner-Str. 9

85521 Ottobrunn

www.asg.ed.tum.de/spm

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: rfa-jobs.rfa@ed.tum.de

More Information

http://www.asg.ed.tum.de/spm