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, please state the course code EGEGR3 with Project: Data-Intensive AI Thermodynamic Models for Next-Generation Building Decarbonisation with Prof Dongfang Liang. Please note that there is a £20 application
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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8060F select ‘Electrical and Electronic Engineering PhD (full time)' as
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the programme code: 8030F · select ‘PhD Chemical Engineering (full time) as the programme of study You will then need to provide the following information in the ‘Further Details’ section: · a
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programme of study: search for the ‘Course Title’ using the programme code: 8030F select ‘PhD Chemical Engineering (full time)’ as the programme of study You will then need to provide the following
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King's College London Department of Engineering | London, England | United Kingdom | about 2 months 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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Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code:8839F select PhD Physics Experimental (Full Time) as the programme of
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8080F Research area: Pure Mathematics select ‘PhD Mathematics (full time)’ as the programme of study You
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8839F select ‘PhD Physics (FT) (Experimental)' as the programme of study You will then need to provide
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for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following
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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