The Post Doc for Sustainable, Reliable and Robust AI throughout the Life Cycle in the Context of Condition Monitoring will be part of an interdisciplinary team in pre-development/corporate research and develop AI-supported solutions for condition monitoring of machines and processes. The aim is to ensure that these solutions are robust, practical and suitable for long-term use. Using methods such as transfer learning, domain adaptation, drift detection and (data and knowledge-driven) hybrid modelling, the postdoc will design and implement workflows for machine learning. The postdoc will also work on real machines and processes to collect data and validate the developed procedures.