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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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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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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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Physiology and Phenomics” at the Department of Plant and Environmental Sciences. The research group is currently composed of the PI, two postdocs (two more will be hired soon), a research assistant and a
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PostDoc in the project). Collaborating with fellow researchers across the UPLIFT network, including those focused on digital twins at DTU Chemical Engineering- As a PhD candidate, your work will adapt
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modellers, molecular biologists and data scientists across IBG-3 and IBG-4 Communicate your science by presenting at conferences, publishing software and peer-reviewed publications Your Profile: Master’s
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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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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
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? Then consider advancing these theories with us. In this project, we aim to extend the powerful tools of statistical mechanics on graph and network models to broader applications in soft and active
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high-impact inventions in analog filters, thermal noise cancelling amplifiers, ultra-low power analog to digital converters, software-defined radio, mixer-first receivers, N-path filters and sub-sampling