879 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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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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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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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
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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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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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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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; designing knowledge-graph-based data models for integrating diverse urban, forest, and market data; developing AI-based forecasting and scenario-simulation pipelines that combine machine learning and
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tools for the design, analysis and evaluation of socially intelligent systems that aim to collaborate with humans in learning and decision-making tasks, often with the aim of improving health. Visit https
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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