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graduates working in a field covered by one of the following Faculties of the University of Cambridge: Architecture, Asian and Middle Eastern Studies, History of Art, Human Social and Political Sciences
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methods to generate complex conformational architectures relevant to sensing, catalysis, and materials science. Successful applicants will have responsibilities in designing, running and analysing synthetic
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different ML architectures for postprocessing precipitation forecasts over India. Determine how to maximise information extracted from the raw forecasts and how to optimise postprocessing skill for heavy
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fields: architecture; building science; mechanical engineering. Possessing a Master’s or PhD degree will be advantageous with prior experience working in the architecture and/or sustainable building design
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methods to generate complex conformational architectures relevant to sensing, catalysis, and materials science. Successful applicants will have responsibilities in designing, running and analysing synthetic
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- the School of Innovation & Technology (SIT) the School of Design, the School of Fine Art and the Mackintosh School of Architecture. The School of Innovation and Technology combines academic study at
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will also contribute to the CAPACITY project, applying tools such as the TIMES-Ireland Model to support robust decision-making on Ireland’s decarbonisation pathways. Applicants must hold a PhD in
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integration. Provide expert-level technical and research support to the Architectural Engineering Group. Contribute to ongoing research projects, funding applications, and spinout activities, including
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and visits to the UK Met Office. HEPPI-ML is one out of several WCSSP-India projects and joint meetings will provide an opportunity for further networking. The successful candidate will hold a PhD, or
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fields: architecture; building science; mechanical engineering. Possessing a Master’s or PhD degree will be advantageous with prior experience working in the architecture and/or sustainable building design