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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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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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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
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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gathering knowledge about the diverse physical and geometric properties of objects and dynamic changes in the environment. This involves leveraging rich sensory data—such as vision and touch—encoding