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profile is shaped in particular by five high-profile areas. About Minds, Media, Machines Minds, Media, Machines (MMM) is one of the five interdisciplinary, high-profile areas that largely define
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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on components of your University Teaching Qualification (BKO) portfolio. Your supervision team will consist of Dr Sanne Weber (main substantive PhD supervisor) and Dr. Haley Swedlund. Would you like to learn more
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logging and/or testing of samples; routine animal husbandry and experimentation, and genotyping May occasionally instruct others in basic laboratory techniques or procedures; Performs related laboratory
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to players’ needs in real time. The successful candidate will work with an interdisciplinary supervisory team, benefiting from expertise in adaptive systems, accessibility and human-computer interaction, and
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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econometric and machine learning frameworks to analyse the causal relationships between transport behaviour, residential energy consumption, and environmental outcomes in urban systems. The successful candidate
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calls. New research areas may be added until the application deadline. Beyond the research conducted during the PhD project, a successful candidate is expected to teach three to four hours weekly during
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knowledge graph from scientific papers and cognitive test questionnaire data, and second, to integrate the graph with transformer-based large language models and causal learning. This offers an explainable
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for place with the projects across the MRC GW4 BioMed3 Doctoral Landscape Award studentships. There are a total of 18 studentships available across the partnership. How do neurons instruct astrocytes