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, efficiency, and the optimisation of material, energy, and waste flows. The main tasks include: 1. Developing Digital Twins: Using data from other work packages, we will create digital twins (DTs) for waste
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include the - to be launched - Smart Data Research UK Social Media Data Access taskforce, a collaboration between Cambridge, Sheffield and York Universities to improve access to social media data
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the PhD has been awarded. Fixed-term: The funds for this post are available for 18 months in the first instance. To apply online for this vacancy and to view further information about the role, please
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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all employees are eligible to live and work in the UK. Further information Apply online
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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the coupled effect on supersonic combustion. This data can then help support future design efforts, which requires validation data where the effects of thermal warpage can be included. To achieve
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nutrition and exercise trials Excellent oral and written communication skills Ability to critically appraise scientific methodology and data Ability to work well individually and as a member of a larger
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives