9 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" Fellowship positions at University of Nottingham
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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Drives Research Institute (PEMC) at the University of Nottingham and become
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About the Role An exciting opportunity has arisen for a talented Researcher to join the world-renowned Power Electronics, Machines and Control Institute (PEMC) at the University of Nottingham and
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unit and individual and collaborative research in the area of Power Electronic, Machine and Control. The role holder will be expected to conduct and lead high-caliber, impactful research at the forefront
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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interviews and the development of a Reuseable Learning Object (Ethics Training Module). The projects represent 50%:50% split across this role. This role provides an exciting opportunity to work with
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. You will also have the chance to teach built-environment researchers about health-risk and epidemiological principles, helping to ensure that design decisions are grounded in sound public-health