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to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements. How to apply You must apply through the University’s Apply
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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device. The project would be ideally suited for someone with a strong chemistry or closely related background and an interest and in analytical and biological chemistry. Supervisor:Dr Nota Zarmpi Entry
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, finance, and healthcare, where data integrity and system reliability are non-negotiable. This PhD project addresses the integration of robust security measures within AI-enabled electronic systems
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qualitative data acquired through focus groups and interviews with regulators, manufacturers and engineers, and deriving analytic insights into material perceptions and values. In addition, they will oversee
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-Based Modelling ✔ Data Science & Advanced Analytics with real-world SCADA data ✔ Renewable Energy Systems & Wind Turbine Engineering ✔ Industry Engagement & Research Commercialization ✔ Scientific Writing
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of the GAG biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working
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quantification and data science. Potential investigation areas: • Enhancing Monte Carlo and Markov Chain Monte Carlo (MCMC) with reinforcement learning. • Developing adaptive tuning and continual learning
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they would design the project (for more information, see the ‘Application procedure’ below). Application Procedure Informal enquiries are welcome and can be made directly to Dr Christiane Ahlborn, Assistant