318 parallel-and-distributed-computing-"U"-"Washington-University-in-St" positions at University of Sheffield
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. (assessed at: application & interview) Desirable criteria Knowledge of computer programming with experience in a scientific program language e.g., Python, Java, C++, C, C#, LabVIEW, MATLAB, Halcon, R, Maple
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fixed-term 301 Tutors Ensure the core Academic Skills programme is cognisant of and responsive to the needs of international students Provide guidance to staff as part of the Elevate staff development
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GIF CDT: A Novel Gas/Liquid contactor for Direct Air Capture and industrial CO2 capture technologies
applications for the following project. This advert will close when a suitable candidate is identified, so early application is encouraged. The CDT boasts an exciting and challenging programme specifically
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workflows, but also by helping to reimagine digital editions beyond the constraints of print-based models. In particular, it researches and analyses how computational and AI-driven methods, including but not
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relevant Cluster Lead a 1-page expression of interest indicating the type of long-term fellowship they would like to apply to; how their research programme would enhance the activities in the School
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critical discourse, Supervise observational or computational astrophysics undergraduate and Masters-level projects professionally and appropriately. Carry out course assessment. This will include marking
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/MSc or equivalent in Computer Science or Software Engineering (assessed at: application/interview). A track record in software testing, testing for autonomous systems, or autonomous driving system
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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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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