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the TDHVL that includes academic staff, postdoctoral researchers, engineers, PhD and undergraduate students. For further details on our laboratory, please see: http://www.highvoltage.ecs.soton.ac.uk/ You
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skills and attributes for success: A PhD (or equivalent) in a relevant subject (Artificial Intelligence, or Data Science), with training or skills relevant to the project (Python-based data collection and
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the TDHVL that includes academic staff, postdoctoral researchers, engineers, PhD and undergraduate students. For further details on our laboratory, please see: http://www.highvoltage.ecs.soton.ac.uk/ You
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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, neutrino experiments, accelerator R&D and data intensive science via our Centre for Doctoral Training. About the role The UCL High Energy Physics Group has an immediate opening for an outstanding PhD
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and team working. The project offers opportunities to apply skills in qualitative data analysis of survey data, complex regression modelling and predictive data analytics. The role You will join an
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reports and presentations High level analytical capability Ability to communicate complex information clearly Informal enquiries can be made to Dr Daniel Wheatley, email: d.wheatley@bham.ac.uk To download
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and team working. The project offers opportunities to apply skills in qualitative data analysis of survey data, complex regression modelling and predictive data analytics. The role You will join an
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continuous systems. The experimental data will contribute to developing an initial techno-economic evaluation to test the feasibility of utilising flower waste as feedstock. The project outcome is a first step
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continuous systems. The experimental data will contribute to developing an initial techno-economic evaluation to test the feasibility of utilising flower waste as feedstock. The project outcome is a first step