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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
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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
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. 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
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learning to communication systems and experimental work is a plus. The project goal is to develop robust transmitter and receiver architectures that can enable distortion-free transmission through a
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surpassing that of state-of-the-art CMOS/SiGe BiCMOS based circuits. This should be achieved by exploiting innovative design techniques and architectures (e.g. gain-boosting strategies and loss-aware power
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different AWE topologies and control architectures impact the reliability and stability of AWE. The research work will be carried out within the AWETRAIN project, where you will be collaborating within a