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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research on an international stage To apply, please submit a complete CV, letter of motivation, university
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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Fraunhofer Institute for Wind Energy Systems IWES | Bremerhaven, Bremen | Germany | about 1 month ago
diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
on particulate and dissolved organic matter from hyperspectral absorption data sampled at Arctic expeditions at AWI’s Hausgarten (Fram Strait) in the last 10 years by optimizing established algorithms from
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms