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our team. We will work towards understanding of the formation of bandgaps in transitional fluid flows and using them to suppress wave-like boundary layer instabilities, thus delaying laminar-turbulent
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into account adequately in models. Therefore, we will work with traditional parameterizations for cloud microphysics, but also explore how physics-enhanced machine learning can help us to develop new ways
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algorithms work restricts their application to problems requiring robust and predictable solutions. Are you driven by a fundamental understanding of reinforcement learning methods and developing new algorithms
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to guarantee network safety and security and to be able to explain (backtrack) in case of failure (explainable AI) *KPN and Delft University of Technology will work together on new ICT technologies (overons.kpn
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Engineering, Mathematics and Computer Science. * KPN and Delft University of Technology will work together on new ICT technologies We are looking for brilliant PhD candidates with a strong interest to the join
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, society and sustainability. This PhD position will be based at the Multimedia Computing Group in the Department of Intelligent Systems (INSY). *KPN and Delft University of Technology will work together on
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related to these areas (naval architecture, marine engineering, aerospace engineering, mechanical engineering, or other related fields). Good spoken and written English and the ability to work in a team are
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period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract
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feasible. This will enable us to improving climate models that can help assessing the effectiveness of climate mitigation and adaptation strategies. In this position, you will work on the forefront
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implementing real-time monitoring with anomaly detection mechanisms. By integrating AI techniques, your work will contribute to enhancing the safety, efficiency, and overall performance of operational aspects