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Field
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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supply and a path to a net-zero-emissions society. SecurEL aims to develop new knowledge addressing research challenges arising from accelerated electrification and increased use of the existing grid
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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of the IMPRS reflects the development of molecular genetics into an information science, based on the plethora of experimental data that are nowadays available and steadily being produced about cellular
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection
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and the role of key architecture components can lead to the development of more efficient and robust training algorithms. This can ultimately result in AI systems that are both more powerful and
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solutions using first motion. Experience in full waveform inversion using innovative tools (e.g. ISOLA) and methods (ML), earthquake location algorithms, computer programming and geophysical equipment
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05.04.2023, Wissenschaftliches Personal We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated