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Field
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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of network defenders, software developers and vendors, security researchers, AI practitioners, and policymakers. You'll get a chance to work with elite AI and cybersecurity professionals, university faculty
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process. Address blind inverse problems by defining a network to learn distortion functions from data, informing the optimization in the learning process. Refine optimization and learning strategies
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energy storage within HVDC networks is a promising response to these challenges. Such integration allows HVDC systems to deliver a broad range of new grid services, including fast frequency response
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-class expertise and supervision, customised training programmes, networking, outreach and career development opportunities, in addition to the standard training and development opportunities
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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International applicants – January 2026 PhD: Applicants for PhD must hold an undergraduate degree at 2.1 level (or non-UK equivalent as defined by Swansea University) in Engineering or a similar relevant science
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driven research Maths competency and experience with statistics in research Software competency: ImageJ, Matlab, Graphpad Prism, R Evidence of Github use An interest in cardiovascular physiology
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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disorders network and through peer reviewed publications. PhD description: Based at the IMH, Nottingham, this PhD will be a jointly supervised mixed-methods project, initially assessing what service key