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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
Large language models (LLMs) can read and write text and code, call tools, and follow instructions. They now allow us to build agents that plan and act over many steps instead of giving a single
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King's College London Department of Engineering | London, England | United Kingdom | about 1 month ago
for Engineering Research (MPhil/PhD) and indicate Dr Francesco Restuccia as the supervisor and quote the project title in your application and all correspondence. Please ensure to add the code [FIREMOD] in
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NILM architectures, a distributed learning framework, and an industrially validated prototype, backed by publications, codes, and a clear path to further development and commercialisation opportunities
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experience. Desirable Attributes Experience working with quantitative and textual data, writing computer code, and/or using existing Digital Humanities tools. The successful candidate will be supported to fill
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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8314F · select ‘PhD Geoscience (full time)' as the
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registered select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8100F · select ‘PhD
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code, like the plastic ends of shoelaces, called telomeres. When cells grow and divide the DNA is incompletely copied, shortening the telomeres. As part of a normal ageing process, when the telomeres
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Website http://www.swansea.ac.uk Street Singleton Park Postal Code SA28PP E-Mail a.u.m.wohlschlegel@swansea.ac.uk Phone 01792602768 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share
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Attributes Experience working with quantitative and textual data, writing computer code, and/or using existing Digital Humanities tools. The successful candidate will be supported to fill gaps in their Digital