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EPSRC PhD Studentship in: Big Data, Network Complexity and Machine Learning to Deliver Targeted Pro-active DWDS Maintenance
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models and determine analytical approaches and modeling techniques to evaluate potential future outcomes. Establish analytical rigor and statistical methods to analyze large amount of data, using advanced
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 15 hours ago
learning, and natural language processing techniques. In addition to advanced analytic skills, this role is also proficient at integrating and preparing large, varied datasets, designing specialized
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: Possess a PhD degree in computer science, electronic engineering, applied mathematics, perception sciences, etc. Background knowledge in signal/data compression, and data-driven and machine learning
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skills are essential for independent day-to-day work. Applicants must have (or be about to obtain) a PhD in a physical or computational science. Desirable fields include atmospheric science, computational
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Generation tools for genome-centric multimodal data integration in personalised cardiovascular medicine (NextGen). NextGen involves 21 organisations across ten different countries in a large-scale and
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community acceptance of large-scale solar farms. The PhD programme offers: Training in the theory for solar energy technologies, experimental measurement and evaluation techniques, tools for modelling and
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management, using enhanced PV energy prediction. Theme 4: To understand what shapes community acceptance of large-scale solar farms. The PhD programme offers: Training in the theory for solar energy
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models (e.g. large-language models) and the analysis of extensive single-cell data across a wide demographic spectrum. This position will allow you to explore and develop new methodologies that integrate
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key role in enhancing the capabilities of our in-house developed OpenScan platform, leveraging generative AI and large language models (LLMs) to process and analyse diverse health data. The role