21 algorithms-"https:"-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" PhD positions in Sweden
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of algorithms, data structures, high-performance computing, machine learning and microbiology. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start
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successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment
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both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates
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artificial intelligence and control systems. In this project, you will design new algorithms for semantic communication between the cloud and autonomous systems—technology that can transform how robots, drones
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usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and algorithms for resource-efficient
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related