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: Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in Geography, Environmental Science, Computer Science, or Engineering. A relevant master’s degree and/or experience
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Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, in the area of performance simulation, analysis, and optimization of supercritical CO2 power generation systems. Cranfield has
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World University Ranking by Subject, it is ranked 20th for Computer Science and Information System, and 21st for Data Science and AI. Edinburgh graduates are ranked 24th in the world by employers
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to develop the new processes, process technologies and green chemistries required for the process industries’ transition to Net Zero. This PhD will focus on scaling up and optimising MEC technology for real
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respond to intense rainfall and enhanced sediment transport. The successful candidate will develop advanced skills in geomorphology, hydrology, environmental data analysis, and climate resilience
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data, you will develop an AI-driven optimisation framework to identify where such interventions can deliver the greatest combined benefits for people and the environment. The research combines urban
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will be based at the University of Cambridge in the Department of Materials Science and Metallurgy as part of the Structural Materials Group. The Structural Materials Group is a diverse and dynamic
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will receive hands-on training in spatial data analysis, while developing conceptual understanding and critical thinking in movement ecology, marine science and conservation. You will build strong
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digesters. The process is stable, well characterised, and is being implemented at scale. It is central to NWL’s nutrient neutrality and net zero ambitions. However, the alga’s biology remains a black box
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code: 8060F · select ‘PhD Electrical and Electronic Engineering (full time) as the programme of study You will then need to provide the following information in the ‘Further Details’ section