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production in the context of circular economy. The research activities in this doctoral thesis are planned with the view of developing a comprehensive multi-perspectives analysis approach, essential to track
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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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simulations to improve on existing power usage models. This research will be a key component of making computing more sustainable by providing novel insights into the energy usage of scientific software and
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involving complex methodologies and statistical analysis. Your responsibilities will include data management, cleaning, and analysis using advanced statistical techniques, as well as drafting reports and
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) in quantitative biology, statistics, or a related discipline, and have experience using statistical modelling and data analysis to address predictive or inferential questions in ecological
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interviews to assess health behaviours. Experience in a variety of qualitative analysis techniques such as thematic analysis and Interpretative Phenomenological Analysis (IPA), in addition to other mixed
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of marginalised communities through documents, interviews, and focus groups to understand their views on health data governance. Additionally, you will also be responsible for managing some organisational elements
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fuels (hydrogen, methanol, ammonia), simulation tools for marine engines and/or fires due to fuel leakages, data analysis methods and their applications for ships, sufficient understanding of appropriate
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of unmodified and modified polymers. If the later, then the overall non- biodegradable component would not be eliminated but would be reduced. 'Smart substitutions'. This explores the possibility that chemical