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deployable Machine Learning (ML) solutions integrated into Industrial Internet of Things (IoT) edge devices for condition monitoring. While ML-driven industrial condition monitoring offers significant
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sustainable design, product development and environmental assessment will conduct case studies to integrate user behaviour into the early design of dishwashers, washing machines, refrigerators and ovens
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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interdisciplinary, applied research with expertise in visualization, design, computer graphics, and the learning sciences. The research nexus for the division is the Visualization Center C, a unique science center in
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We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
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Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
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Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics” - a multidisciplinary research effort at the intersection of machine learning and materials science. This
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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aims to advance the field of time and frequency (TF) transmission in data communication networks. The focus of the research will be on distributed fiber optic sensing (FDOS) and machine learning