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equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in
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plus RF and microwave engineering. Hands-on experience with software defined radios (SDRs) like USRPs is considered a plus Statistical signal processing Resource allocation and optimization
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digital technologies. At HPI, you benefit from close supervision by experienced professors and postdocs, cutting-edge research facilities, and a collaborative academic network, e.g. with the University
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energy projects. About 2XE 2XE is an award-winning South Australian consultancy committed to guiding companies towards sustainable growth and achieving net-zero emissions. Leveraging a robust blend of
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collegial respect and academic freedom tempered by responsibility. We develop talent by offering national/European and global networking opportunities, unique research infrastructures, and a collaborative
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In...
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technologies. At HPI, you benefit from close supervision by experienced professors and postdocs, cutting-edge research facilities, and a collaborative academic network, e.g. with the University of Cape Town (UCT
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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, the internal workings of deep neural networks remain largely mysterious, posing a significant challenge to the interpretability, reliability, and further advancement of these models. This project seeks deep