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will also design and develop new software and prototype models. Research areas: Computer science, Simulation-based automated synthesis and verification of human physiology models, Artificial intelligence
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Twins As a PhD candidate, your goal is to ensure the integrity, synchronization, and seamless integration of this vital multimodal data. You will be at the forefront of developing the automated, robust
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employ multiple strategies. On the one hand, it can draw upon its own knowledge acquired through past experiences to extrapolate the consequences of ongoing events or predict the outcome of its actions. It
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machine learning potentials to rapidly generate new condensed phase training data, ii) develop automated workflows to train molecular mechanics force fields against these accurate data sources, and iii
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generation sequencing Applying machine learning-guided directed evolution to improve multiple enzyme properties Upscaling selected biotransformation reactions in collaboration with academic partners
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investigate how public agencies adopt and integrate AI technologies, what forms of automation and augmentation emerge, and how these developments influence organizational structures, professional roles, and
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. · Automate processes and explore state-of-the-art solutions for filtering, noise reduction, and kernel-based techniques. · Present your findings at academic conferences and publish research in peer
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monitoring. To address these limitations, the proposed research will integrate UAV-based imaging, satellite remote sensing, and AI-supported classification workflows to quantify lichen distribution at multiple
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—an essential technology to meet the ultra-fast, deterministic needs of future applications like autonomous driving, smart cities, and industrial automation. About the TeraWireless Project The TeraWireless
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at