558 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs at University of Sheffield
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silk extrusion, which will guide attempts to produce synthetic silk in the lab. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes
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selecting appropriate materials, designing components for 3D printing or machining, and integrating rotating machinery and porous membranes into a functional experimental setup. Apply advanced laser-based
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information: https://www.sheffield.ac.uk/postgraduate/phd/scholarships Loans are available to eligible home fee-paying doctoral students studying postgraduate research courses: https://www.sheffield.ac.uk
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for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes Self or externally funded students only. References https://www.sheffield.ac.uk/biosciences/research
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Reinforcement Learning from Human and AI Feedback (S3.5-COM-Peng) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Bei Peng, Dr Zheng Yuan Application
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Machine Learning techniques. As Research Associate you will have a research leadership role in the group, and will assist in day-to-day supervision of post-graduate research students. You will collaborate
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universities. We are always looking to work with talented and motivated scientists. Funding Notes This project is for Self-funded students or students with external funding. References https://sheffield.ac.uk
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Optimisation of powder processing routes for plutonium disposition: impacts of milling and additives
instrumentation for materials formulation, processing, characterisation and performance assessment. More information on these facilities can be found at: · https://www.sheffield.ac.uk/royce-institute
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. Manage distribution and return of keys/fobs for accommodation buildings including cycle storage and car parking permits. Support the management and auditing of 9,000 building keys, including daily and
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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