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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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, 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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collaborate with researchers at Ludwig Maximilian University, Munich and Centre Algatech, Trebon, Czech Republic, as part of the Synergy research programme. The aims of the Sheffield part of the Synergy
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/groups of students and programme directors. Undertake module evaluation, including facilitating student feedback, reflecting on own teaching design and delivery; and implementing ideas for improving own
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workforce training, and computer-integrated systems, has become the primary pathway for transforming and upgrading manufacturing industry in the coming decades. Real time monitoring of cutting tool conditions
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processing, data analysis, data-driven modelling, optimisation and computation algorithms, machine learning models and neural network structures, as well as strong skills and experiences in computational
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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