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fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
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Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage
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-offs between the modularity (henceforth interpretability) and the efficiency in existing end-to-end modular autonomous driving models. In this PhD project, student is expected to conduct research in
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model with each SNP independently, perhaps adjusting for other covariates such as age and sex. This project will focus on developing and applying novel machine learning and AI methods to improve
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Testing AI/LLM systems Primary supervisor Yongqiang Tian Research area Software Engineering In
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I am seeking PhD candidates interested in working on designing Learning Analytics innovations to study classroom proxemics by analysing and visualising indoor positioning data (along with other
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As a pregnancy approaches term (the point at which the foetus is considered fully developed), decisions are made about the timing of birth and the way babies are born. These decisions are incredibly challenging for clinicians and pregnant women. Digital health records, advances in big data,...
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the University’s research capacity in a globally relevant field. The role provides the opportunity to develop and publish a monograph based on Korean Studies-related PhD research or, if already published
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quantification in various biological matrices by quantitative LCMS/MS methods. This role will include examination of key physicochemical properties using a range of analytical instrumentation and standard
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer science