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”. This exciting opportunity involves leading the development of advanced data-driven mathematical and computational models to suppress turbulence in pipe flows, contributing to pressing engineering efforts toward
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. Research in the group is a mixture of experimental and computation work. Research tools to be used are likely to include lab and pilot scale experimentation. You will use the state of the art
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Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application
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contexts. The project will build on both consolidated knowledge in the history of technologies, and the most recent literature on the perception of digital and computer-assisted creative outputs
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. This PhD project is set within the Fusion Engineering CDT at The University of Sheffield. Students will receive a 3-month training programme in fusion engineering at the start of the course, delivered across
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. Identify, create and provide a training and development programme tostaff on contracts and contract negotiation. Develop and implement an efficient contracting process, including an appropriate, transparent
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, reactor design and computer programming. Entry requirements: Upper second class degree in Chemical Engineering, Materials Science and Engineering or Chemistry. Funding Notes Department contribution (fee
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-resolution imaging and reconstruction of neural tissues (see https://ist.ac.at/en/research/siegert-group/). Leveraging computational tools such as machine learning and topological data analysis, we will
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Notes Studentships cover tuition fees, a tax-free stipend and consumables for the duration of the 3.5 year programme. The stipend rate for the academic year 2024/25 is £19,237. The stipend will rise with
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reference the application criteria in the application statement when you apply. Essential criteria Postgraduate qualification in a relevant subject such as a PhD or MSc in Psychology, Data Science, Computer