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Field
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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information on the admissions process generally, please visit our How to Apply for a Research Degree webpage or contact the Doctoral College . Applications will not be considered if information is missing
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk
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. Further information about the University can be found here The Role and Department The School of Education at Durham University is a leading centre for educational research and teacher development, with a
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. Daily activities include coding, data analysis, simulation modelling, and collaboration with industry partners. Some travel to manufacturing facilities and conferences may be required. This funded PhD
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conducting the qualitative interviews with patients and analysing the interview data. You will be presenting that data to the study team at regular meetings and contributing to the intervention and app
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for automotive applications” BCAST is a specialist research centre in metallurgy with a focus on processing of metallic materials for lightweighting applications. See www.brunel.ac.uk/bcast for more information
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the spaces, but also behavioural changes, such as changing habits regarding ventilation or heating. The second part will employ secondary data analyses from existing cohort studies to explore the associations
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purified polysaccharides for promising functional profiles (based on comparing to baseline data established for currently used polymers). The choice of polysaccharides would be guided by prior knowledge