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Field
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platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions for distribution electric
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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal
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these findings should be used to design AI agents that actually warrant our trust. You can find more information about our work and approach at the Project Website: https://research.kent.ac.uk/trust-moral-machines
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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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the real-time simulation platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions
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language, you'll need an IELTS score of 6.5 or equivalent with no individual element below 5.5. How to apply: Applicants must register on SGSSS Apply, completing their Equal Opportunities data. Applicants
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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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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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: For an application to be completed, candidates should also fill in the following online form: Diversity data form (link to Microsoft Form to be completed by the candidate) Applications must be submitted by
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. This research will use distributed field data collection (macroinvertebrates, sediment character and dynamics) and a complementary set of flume experiments to quantify these impacts and to systematically