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Chiara Manfletti

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PhD Position in Fault Detection and Isolation for Rocket Propulsion Systems – Chair of Space Mobility and Propulsion, Technical University of Munich Technical University of Munich in Germany

Degree Level

PhD

Field of study

Mechanical Engineering

Funding

Full funding available
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Country

Germany

University

Technical University of Munich

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Keywords

Mechanical Engineering
Aerospace Engineering
Fluid Mechanics
Python Programming
Fault Detection
Robotics
Rocket Propulsion
Embedded System
Thermodynamic
Machine learning

About this position

The Chair of Space Mobility and Propulsion at the Technical University of Munich (TUM) is offering a fully funded PhD position focused on Fault Detection and Isolation (FDI) for rocket propulsion systems. The research is embedded within the REACT project, a 3-year Horizon-Europe funded collaboration aimed at developing autonomous fault management solutions for reentry capsule propulsion systems. The successful candidate will join a dynamic team working on ASCENT, a vertical takeoff and landing (VTVL) hopper with a bi-liquid propulsion system, and collaborate with industry partners Orbital Paradigm and Klepsydra Technologies.

Key responsibilities include analyzing failure modes for rocket propulsion systems, contributing to the definition of FDI system specifications, developing and evaluating model-based and machine learning-based FDI algorithms, and validating these algorithms experimentally on the ASCENT propulsion test bench. The role involves close interaction with functional engineers from partner organizations, collaborative project management, and contributions to technical, administrative, and financial reporting. The candidate will also lead hardware-in-the-loop test campaigns and participate in the design, commissioning, and operation of the ASCENT system.

Applicants should hold a Master of Science or Engineering degree with excellent results in Aerospace Engineering, Control Engineering, or a related field. Strong fundamentals in thermodynamics and fluid dynamics, experience in coding (especially Python), and proficiency in modelling and simulation based on ODEs are required. Experience in conducting experiments, control engineering, and machine learning is advantageous. The position requires high motivation, independence, strong collaboration skills, excellent English communication, analytical and problem-solving abilities, and organizational proficiency.

The PhD position offers a full-time contract (100% / 40h, pay grade E13, TV-L) for three years, with the goal of obtaining a Dr.-Ing. degree. Benefits include flexible home office solutions, 30 days of paid holidays, opportunities to publish in top-tier journals and conferences, and the chance to contribute to cutting-edge research in space mobility. TUM values diversity, equity, and inclusion, and encourages applications from underrepresented groups and individuals with disabilities. The position is suitable for disabled persons, who will be given preference in case of equivalent suitability.

To apply, candidates should send their application (CV, motivation letter, transcripts, and supporting documents) via email to [email protected] (preferably as a single PDF). The vacancy will remain open until filled, with an expected start date in July 2026. Applicants are advised to review the TUM privacy policy regarding personal data processing before submission. For further information, visit the Chair of Space Mobility and Propulsion website at https://www.asg.ed.tum.de/spm/startseite/ or access the application portal directly at https://portal.mytum.de/jobs/wissenschaftler/NewsArticle_20260423_090526.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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