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will generate unprecedented volumes of data, to be processed at a central facility, and distributed to a global network of SKA Regional Centres (SRCs) for storage, access, and scientific exploration
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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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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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, 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
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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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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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Fixed-term: The funds for this post are available for 12 months A position is available for a Postdoctoral Research Associate (Postdoc) in the forthcoming Aspirational Computing Lab in
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Assoc Prof Liton Kamruzzaman, Prof Hai Vu, Prof Graham Currie, Prof Eric Miller (University of Toronto), and Prof Roger Vickerman (University of Kent). Together, the team aims to: Define sustainable size
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process