896 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions in Sweden
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, both over the wireless interface and within the core network, will be driven by AI and machine-learning applications. This research will develop efficient communication strategies to support
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Umeå University is offering a PhD position in Computing Science with a focus on machine learning for graph
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We are looking for a postdoc to join our team at the Division of Computer and Network Systems. Become part of our innovative group and contribute to exciting research in Computer Architecture within
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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. The candidate is expected to have an overall interest in AI concepts and methods, in particular human-centred AI, and expertise in formal models and machine learning, as demonstrated by publications and other
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position as Senior Lecturer. Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep
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for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high-performance on cross-vendor GPUs, we aim to create new techniques for global illumination and material models. The subject works with