333 postdoc-parallel-computing positions at University of Sheffield in United Kingdom
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industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modelling. Research Objectives will focus on: (a) Enhancing CoronaScreen by
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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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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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/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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. 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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. 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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. 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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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