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, algorithms, and experiments on multimode mechanical quantum platforms (circuit quantum acoustodynamics with transmon–HBAR devices; HBAR arrays; microwave optomechanics). The postdoc will work at UiO with
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mathematical structures and computational algorithms underlying modern machine learning and artificial intelligence. Relevant themes include geometric and algebraic methods for learning, structure-preserving
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the QuantERA project ‘QM3L - Quantum protocols for Multimode Mechanics advanced by Machine Learning’, a European consortium combining theory, algorithms, and experiments on multimode mechanical quantum platforms
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Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance the understanding of high-dimensional neural activity patterns. The successful
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. Theoretical activities include research on quantum information theory, quantum algorithms, quantum engineering, many-body theories for quantum technologies, quantum machine learning, and fundamental quantum
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, or quantum information science, including quantum information theory, quantum error-correction, quantum computing and communications, and quantum algorithms. As an integral part of the research, the successful
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. Integreat develops theories, methods, models, and algorithms that combine data with general or domain-specific knowledge, helping lay the foundations for the next generation of machine learning. Integreat
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artificial intelligence (AI) and an increasingly important force in a digital and data-driven world. Integreat develops theories, methods, models, and algorithms that combine data with general or domain
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National Lab, University of Tokyo etc.), the PhD candidate is expected to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient
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science can be eligible if they possess significant, demonstrable experience with optimization using physics-inspired algorithms or quantum computing frameworks. The applicant must have submitted his/her