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PhD/Postdoc Position for Safe Artificial Intelligence for Maritime Engines
PhD/Postdoc Position for Safe Artificial Intelligence for Maritime EnginesTechnical University of Munich • Munich, DE
PhD / Postdoc Position for Safe Artificial Intelligence for Maritime Engines

PhD / Postdoc Position for Safe Artificial Intelligence for Maritime Engines

Technical University of Munich • Munich, DE
Vor 30+ Tagen
Stellenbeschreibung

PhD / Postdoc Position for Safe Artificial Intelligence for Maritime Engines

14.11., Wissenschaftliches Personal

The research group Cyber-Physical Systems of Prof. Matthias Althoff at the Technical University of Munich offers a PhD / Postdoc position in the area of safe artificial intelligence for maritime engines. The Technical University of Munich is one of the top research universities in Europe fostering a strong entrepreneurial spirit and international culture.

Expected Starting Date : February - May

Closing Date for Applicants : 05 January

Duration : 3 years with a possible extension (individual duration for Postdocs).

Project and Job Description

Integrating artificial intelligence into maritime engines powered by alternative fuels like hydrogen significantly enhances operational efficiency and reduces emissions. AI systems can continuously analyze real-time data—such as engine load, fuel flow, and environmental conditions—to optimize combustion and propulsion strategies. This dynamic adjustment ensures that hydrogen, with its unique properties like high flame speed and low ignition energy, is used as efficiently as possible. As a result, vessels can achieve lower fuel consumption and drastically reduce greenhouse gas emissions, aligning with global decarbonization goals set by the International Maritime Organization. Moreover, AI can simulate and evaluate countless operational scenarios, helping ship operators make informed decisions that balance performance with sustainability.

Equally important, AI helps ensure that hydrogen-fueled engines operate within the strict physical and mechanical constraints inherent to maritime propulsion systems. Hydrogen poses challenges such as pre-ignition risks, material compatibility, and storage under high pressure. To address these challenges, we will develop novel techniques for provably safe reinforcement learning. This project is conducted in close collaboration with Everllence (formally known as MAN Energy Solutions). The developed methods have to be tested in simulation and on real engines.

Previous Work

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.

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Artificial Intelligence • Munich, DE

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