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- University of Oslo
- University of Bergen
- UiT The Arctic University of Norway
- University of Agder
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of South-Eastern Norway
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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Field
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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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responded to past climatic warming at the Pleistocene–Holocene transition. Range expansions and demographic change leave signatures in the genome, including changes in genetic diversity and in how genetic
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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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. 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