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; trying to understand why certain elements are more abundant than others; or how the different populations of stars in globular clusters arose. How can we better approximate mixing during core He burning
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stellar interiors, birth properties of black holes and neutron stars, supernova light curves and spectra, gravitational waves, neutrino astrophysics, the production of heavy elements stellar explosions, and
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Contextual Data Analytics (ICDA) as a method to address contextual analysis challenges by bringing rich contextual information to the analyst’s workspace. Despite the technological capability to support ICDA
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This Ph.D. project aims to combine causal analysis with deep learning for mental health support. As deep learning is vulnerable to spurious correlations, novel causal discovery and inference methods
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while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis
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component involving medical practicioners and providers, and also network / telecoms providers, to collect the required datasets of applications, services, and geographically available QoS data. The technical
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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Identifying vulnerabilities in real-world applications is challenging. Currently, static analysis tools are concerned with false positives; runtime detection tools are free of false positives but
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inform or design future experiments. As a researcher in my group, you would not only develop imaging theory and analysis tools to answer science questions about where the atoms are, what they are, and how