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The Engineering Risk Analysis Group is looking for a

Research Associate (PhD candidate) for AI-based Infrastructure Maintenance Planning

28.12.2021, Wissenschaftliches Personal

The Engineering Risk Analysis Group at TUM offers a fully funded PhD position on the topic of AI-based Infrastructure Maintenance Planning within the project INFRA-RELEARN funded by the TUM Georg Nemetschek Institute of Artifical Intelligence for the Built World.

The Engineering Risk Analysis (www.cee.ed.tum.de/era/) develops and implements engineering reliability, risk & decision analysis to enhance optimal & sustainable decision making for civil systems and the environment. There is a tremendous potential in exploiting artificial intelligence and digitalization to enhance and optimize maintenance of civil infrastructure systems, including transportation, energy and water networks.

We offer a fully funded PhD position (100% TV-L E13) within the INFRA.RELEARN project, financed by the TUM Georg Nemetschek Institute of Artificial Intelligence for the Built World. In this project, we are developing strategies for optimizing infrastructure maintenance through reinforcement learning. The position is part of a team of civil engineers and computer scientists.

Your profile:

  • M.Sc. degree in Civil, Mechanical or Electrical engineering. Other relevant qualifications will be considered.
  • Experience with machine learning and probabilistic methods (completed Master-level course in quantitative risk analysis, probabilistic modelling and assessment, or equivalent)
  • Experience in programming with MATLAB, Python or equivalent
  • Excellent analytical skills, strong interest and capabilities in quantitative analysis
  • Proficiency in English (both written and oral), German is a plus
  • Strong communication skills

We offer full employment with payment according to TV-L E13, with contract duration limited to 4 years. Earliest starting date is February 1, 2022. The successful candidate will be enrolled in the doctoral program of the Technical University of Munich. You can expect a dynamic and flexible work environment. We are located in the centre of Munich.

If you are interested in this position, please send your CV and a short cover letter to: elizabeth.bismut@tum.de.

TUM is aiming to increase the number of women employees, and applications from women are expressly welcomed. People with disabilities, with essentially the same suitability and qualification, will be preferred.

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: elizabeth.bismut@tum.de