-
universities, and three research and technology organizations—you will be at the forefront of shaping the future. This PhD project offers you the opportunity to develop cutting-edge competencies in digital
-
. Qualifications You should have completed a two-year master's degree (120 ECTS points) in Civil, Architectural, Environmental, Electrical, Mechanical or Industrial Engineering, Autonomous Systems, Computer Science
-
to correlate with improved generalization. Likewise, the behavior of neural networks is influenced by architectural choices and various training techniques applied during learning, known as inductive bias
-
integration. The focus will be advanced packaging and integration mechanisms for wide-bandgap power devices and passive components (magnetics and capacitors), as well as innovative power delivery architectures
-
to mutual agreement. We seek a motivated, curious, and outgoing PhD candidate with a solid background in fiber-optics, communication engineering and machine learning. Experience with application of machine
-
Network” (AWETRAIN). Airborne Wind Energy (AWE) is a radical new technology based on tethered aircraft generating electricity from altitudes higher than conventional wind turbines. This allows