172 learning-"https:"-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" PhD positions in Germany
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- cellumation GmbH
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Field
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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dedicated to advancing cognitive robotics. The network trains early-stage researchers to develop robots that can interact, learn, and adapt in real-world environments while ensuring quality, safety, and
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Beginning Winter semester Application deadline All students – online application: 1 March for the following winter semester https://www.lmu.de/psy/de/studium/doctoral-training-program-in-the-learning-sciences
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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, motivation to learn new skills to expand scientific knowledge Excellent communication skills and ability to work in an interdisciplinary team Very good written and oral communication skills in English (at
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laboratories Based on the complexity of the project, motivation to learn new skills to expand scientific knowledge High degree of analytical working style Excellent communication skills and ability to work in an
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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optimization. In this context, interdisciplinary research is strongly encouraged—particularly collaborations spanning computer science, computational linguistics, cognitive science, and the learning sciences
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Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be able to teach you missing skills during your induction. Our Offer: We work on the very
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical