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written English is required. A real passion and commitment for research. Desirable criteria are: Knowledge of a variety of deep learning architectures and methods. Knowledge or past work on explainability
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diverse expertise and collaborative partnerships to foster innovative and socially engaged doctoral research. The award supports new and emerging themes across art and humanities, architecture, design, and
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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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, Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS
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receive mentoring and outstanding training in modern crop genetics, genomics, data analysis, and bioinformatics. The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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would approach the project and what methods you would use. Under Campus, please select ‘Loughborough’ and select programme ‘Architecture, Building and Civil Engineering’. Please quote the advertised
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architectures (cassette and containerised). Use CFD modelling and lab pilots to optimise hydraulics, mass transfer, and electrode configurations. Energy Integration Quantify full energy balances of MEC operation
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research plan for the ARTS Doctoral programme soon after being hired. The target graduation time in doctoral studies is four years at the School of Arts, Design and Architecture. You can find more
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pathways can be combined to make MECs economically and environmentally viable at scale. Research Aims: Process Intensification & Scale-Up Design and evaluate scalable MEC architectures (cassette and