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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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, computer science, computational biology and computational statistics. More information about us, please visit: Department of Mathematics . Project description We seek to recruit a PhD student for the following
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data-driven production planning affect industrial sustainability—from economic, environmental, and social perspectives. Your work assignments: Conduct life cycle cost analyses (LCC) to assess
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departmental duties, up to a maximum of 20% of full-time. Your qualifications We are searching for someone with a Master’s degree in computer science, media technology, computer engineering, human-computer/robot
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to altered patterns of gene expression. We have assembled a unique data set of three independent lineages of Italian sparrow Passer italiae and their parental species, with data on gene expression and tissue
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on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.The
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mathematical modelling and data science with diverse disciplines, including ecology, plant physiology, and molecular biology. Your research will deepen our understanding of how living systems respond to stress