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the Quantum Optics, Quantum Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) - one of the largest quantum hubs in
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the Quantum Optics, Quantum Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) - one of the largest quantum hubs in
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Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian
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Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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: 30,00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 30.04.2029 Job ID: 5311 The work group Machine Learning with Graphs of the subunit Data Mining and Machine
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applications of macrosopic quantum coherence in levitated solidstate platforms. Our Team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member
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Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian
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of macrosopic quantum coherence in levitated solidstate platforms. Our Team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member of the Vienna
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energy systems. The PhD project focuses on innovative cooling solutions for high-power data centers and high-performance electronic systems.As current server and data center infrastructures primarily rely