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different types of applications (e.g., medical imaging). The work will be both theoretically oriented, as well as focused on implementation of experiments with machine learning algorithms for
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. Project description Machine Learning – Algorithms and Theoretical Foundations Recent advances in AI have highlighted the potential of learning systems that make sequential decisions and adapt to
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the design, implementation, and evaluation of artifacts that integrate immersive experiences across the XR spectrum (augmented, virtual, and mixed reality) with real-time machine learning algorithms
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analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems. Project description Control Engineering and Instrumentation are growing in
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involve writing and running code to process sequencing data on a computer server, applying statistical models and machine learning algorithms, and performing downstream data analysis, including
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information security by developing novel methods, algorithms, system architectures, and evaluation frameworks for securing modern intelligent and distributed systems. The project lies at the
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Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools for human-centered intelligent realities, to lead the way for
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involve developing and applying high-fidelity CFD models of turbulent flows in hydraulic turbines, integrating machine learning and deep reinforcement learning algorithms with numerical simulations
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workday might involve writing and running code to process sequencing data on a computer server, applying statistical models and machine learning algorithms, and performing downstream data analysis
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on social media. Large language models are used to analyze polarizing communication in text and audio from Sweden and Finland at scale, and experiments test how forms of communication and algorithms