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Field
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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-service involvement, develop typologies of need, and uncover spatial and temporal trends. Combining data science techniques with stakeholder engagement, the project aims to generate actionable insights
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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the population from infectious diseases and other hazards. UKHSA does this by monitoring infectious disease trends and outbreaks using systems that collect information over time and allow unusual changes to be
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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Evaluating the use of longitudinal over-the-counter healthcare sales data as a source of syndromic surveillance for community-based infections UK Health Security Agency and Nottingham University
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Research Abstract: This project aims to address the challenges in robot inspection, which is one of the key applications in future robots. Often, as part of the inspection, robots collect various data
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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Project description: Reliable, high-resolution electricity demand data are scarce across the global south, limiting our understanding in these regions of the relationship between weather and energy demand
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Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Research theme: "Materials Characterisation" "Data Science and Machine Learning in