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Field
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system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models and machine
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. The resulting dataset will be analysed using Structural Equation Modelling (SEM) to quantify the relationships between these factors and uncover both direct and indirect pathways affecting behaviours
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fluorescence microscopy to follow in real-time how nanomedicines engage with living cell membranes (and simpler model systems) and quantify these interactions. Similar studies can be performed for understanding
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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join a vibrant, supportive research community (around 20-25 people involved in fluids modelling research). Collaborate with the Leonardo Centre for Tribology: Work with top researchers on experimental
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source, has implications for heat network demand and electricity network demand. To model the implications of widespread adoption of new technologies, requires new demand profiles which these networks will
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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve
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with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the