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Field
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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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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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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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Requirements We will only consider candidates with a good Bachelor’s degree (ideally, a first, minimum 2:1) and/or a master’s degree in computer science, data analytics, health economics, or computational
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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
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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data
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. Develop analytical and finite element (FE) models to investigate the extent and sources of nonlinear behaviour in LGSs. 3. Develop novel control strategies to stabilise LGS shape, orbit & attitude
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place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills and strong verbal and written communication skills are also essential
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manufacture. The PhD candidate will gain expertise in gene therapy production as well the experimental and computational steps required to capture and analyse transcriptional data at single cell resolution
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can be set up in one day. During the plant growth period the student will be trained in the appropriate analytical skills for analyses after concluding the trial (2 weeks). Scope for initiative