455 computer-programmer-"Multiple"-"O.P"-"U"-"U.S" positions at University of Sheffield
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driving through deep reinforcement learning. Computing demands can grow rapidly with such models, so a significant aspect of the research is in formulating the problem in a tractable form, and application
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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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data communication (assessed at: application/interview) Ability to work under own initiative to agreed protocols and deadlines, and to plan and progress work activities (assessed at: application
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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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/October 2025. This will consist of an interview, presentation and campus tour. We plan to let candidates know if they have progressed to the selection stage in September 2025. If you need any support
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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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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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and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics