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- University of Oslo
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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
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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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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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status - expressed through markers such as likes, ratings, endorsements and algorithmic signals - is created, interpreted and translated into social and economic advantages. The project uses a multi-method
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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
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background in computer science can also be eligible if they possess significant, demonstrable experience with optimization using physics-inspired algorithms or quantum computing frameworks. The applicant must
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algorithms is anticipated in mainland Norway, Svalbard, and abroad. Funding is also available for conference attendances and research visits with external collaborators. The position is part of the ERC-funded
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several