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a unique opportunity to influence and develop the Faculty’s curriculum and research training programs, thereby shaping the future of educational research and practice. This position demands a special
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these issues is critical for building trustworthy multimodal AI systems. Research Objectives The goal of this PhD project is to develop scalable Bayesian uncertainty estimation frameworks for single- and multi
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the evolution of massive binary stars into compact binaries as sources of gravitational-waves and astrophysical inference on gravitational-wave observations. My research group on massive binary evolution -- also
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internal and external partners to support the ongoing management and development of the University’s property assets. This opportunity will suit a candidate with experience in retail, commercial or mixed-use
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is carried out within the LHCb collaboration that runs one of the four large experiments at the Large Hadron Collider at CERN as well as towards future collider developments. I supervise a number of
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I supervise projects in particle physics. My main emphasis is on phenomenology, comparison of predictions with experimental measurements. I follow developments in flavour physics: weak decays
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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for examining and imaging the magnetic fields from exotic conducting materials (e.g. superconductors, topological insulators), performing high bandwidth and high sensitivity vector magnetic sensing and developing
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A research-only academic is expected to contribute to the University’s research effort while developing their research expertise through the pursuit of defined research projects relevant
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the brain. This wouldn't be a typical machine learning PhD, as many aspects can only be examined on a philosophical and theoretical level. There may be scope to implement aspects in the ideas you develop